{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}D:\Dropbox\Harvests and Protests\Data&code\PSRM_ReplicationSubmitted\LogFile.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}29 Sep 2023, 19:33:22

{com}. do "C:\Users\babak\AppData\Local\Temp\STD00000000.tmp"
{txt}
{com}. 
. *** START
. use "AllDataMerged_15May2023_weighted.dta", clear 
{txt}
{com}. 
. 
. // rename a few variables 
. gen idle_index = IDLE_index
{txt}(34,944 missing values generated)

{com}. gen ym = date_month
{txt}
{com}. lab var idle_index "Idle Index"
{txt}
{com}. 
. // set panel structure
. xtset objectid ym
{res}{txt}{col 8}panel variable:  {res}objectid (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}ym, 360 to 695
{txt}{col 17}delta:  {res}1 unit
{txt}
{com}. 
. gen SCADantigov = 0
{txt}
{com}. replace SCADantigov = 1 if n_etype8>0 | n_etype9>0 
{txt}(3,772 real changes made)

{com}. replace SCADantigov = . if n_etype8==.
{txt}(0 real changes made)

{com}. 
. btscs SCADantigov year objectid, g(py_SCADantigov)
{txt}
{com}. 
. gen py2  = py_SCADantigov*py_SCADantigov
{txt}
{com}. gen py3  = py_SCADantigov*py_SCADantigov*py_SCADantigov
{txt}
{com}. 
. ***************************************************************************************
. ***************************************************************************************
. ** Figure 1: Distribution of Idle Index
. ***************************************************************************************
. ***************************************************************************************
. 
. reghdfe SCADantigov idle_index , absorb(objectid ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 242204{txt}){col 67}= {res}     11.82
{txt}{col 51}Prob > F{col 67}= {res}    0.0006
{txt}{col 51}R-squared{col 67}= {res}    0.0780
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0753
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0000
{txt}{col 51}Root MSE{col 67}= {res}    0.1177

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0031646{col 26}{space 2} .0009203{col 37}{space 1}    3.44{col 46}{space 3}0.001{col 54}{space 4} .0013608{col 67}{space 3} .0049684
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0136895{col 26}{space 2} .0004929{col 37}{space 1}   27.77{col 46}{space 3}0.000{col 54}{space 4} .0127234{col 67}{space 3} .0146556
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}

{com}. gen sample = 1 if e(sample)==1
{txt}(34,944 missing values generated)

{com}. 
. hist idle_index if sample==1 , scheme(s1mono)  percent ytitle(% of Observations) color(green%60) name(hist, replace) bin(20)
{txt}(bin={res}20{txt}, start={res}1.118e-08{txt}, width={res}.05{txt})
{p 0 4 2}
{txt}(note:  named style
green % 60 not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
green % 60 not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
green % 60 not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
green % 60 not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
green % 60 not found in class
color,  default attributes used)
{p_end}
{res}{txt}
{com}. //graph export "Idlehist.pdf", replace
. 
. tabstat idle_index if sample==1 , by(mon)

{txt}Summary for variables: idle_index
{col 6}by categories of: month 

{ralign 6:month} {...}
{c |}      mean
{hline 7}{c +}{hline 10}
{ralign 6:Apr} {...}
{c |}{...}
 {res} .4948868
{txt}{ralign 6:Aug} {...}
{c |}{...}
 {res} .5605845
{txt}{ralign 6:Dec} {...}
{c |}{...}
 {res}  .465768
{txt}{ralign 6:Feb} {...}
{c |}{...}
 {res} .5979949
{txt}{ralign 6:Jan} {...}
{c |}{...}
 {res} .5351448
{txt}{ralign 6:Jul} {...}
{c |}{...}
 {res} .4768956
{txt}{ralign 6:Jun} {...}
{c |}{...}
 {res} .3581925
{txt}{ralign 6:Mar} {...}
{c |}{...}
 {res} .5561058
{txt}{ralign 6:May} {...}
{c |}{...}
 {res} .4414798
{txt}{ralign 6:Nov} {...}
{c |}{...}
 {res}  .402341
{txt}{ralign 6:Oct} {...}
{c |}{...}
 {res}  .398261
{txt}{ralign 6:Sep} {...}
{c |}{...}
 {res}  .510279
{txt}{hline 7}{c +}{hline 10}
{ralign 6:Total} {...}
{c |}{...}
 {res} .4831611
{txt}{hline 7}{c BT}{hline 10}

{com}. graph bar (mean) idle_index if sample==1, over(Month, ) bar(1, fcolor(navy%60)) scheme(s1mono) ytitle(Mean Idle Index)  title(Mean by Month, size(medium)) name(meanovermon, replace)
{res}{p 0 4 2}
{txt}(note:  named style
navy % 60 not found in class
color,  default attributes used)
{p_end}
{res}{txt}
{com}. ///scatter cultivated idle_index if sample==1 , ytitle("% of cultivated land") scheme(s1mono) name(cult, replace) msymbol(oh) mcolor(red%30)
> 
. graph combine hist meanovermon, scheme(s1mono)
{p 0 4 2}
{txt}(note:  named style
green % 60 not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
green % 60 not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
green % 60 not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
green % 60 not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
green % 60 not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
navy % 60 not found in class
color,  default attributes used)
{p_end}
{res}{txt}
{com}. graph export "FigTbl/Fig1_Idlediag.pdf", replace
{txt}(file FigTbl/Fig1_Idlediag.pdf written in PDF format)

{com}. 
. 
. ***************************************************************************************
. ***************************************************************************************
. ******** Figure 2: see DoFile_CreateMap_11Sep2020.do
. ***************************************************************************************
. ***************************************************************************************
. 
. 
. ***************************************************************************************
. ***************************************************************************************
. ******** Table 1: Agricultural idle time and armed conflict 
. ***************************************************************************************
. ***************************************************************************************
. 
. 
. ** SCAD analysis:
. 
. egen yearmon = group(year mon) 
{txt}
{com}. egen oyfe = group(objectid year)
{txt}
{com}. // gen object year FE
. 
. //gen lnpy_SCAD = ln(py_SCADantigov+.1)
. 
. 
. est clear 
{txt}
{com}. sum SCADantigov if sample==1 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}SCADantigov {c |}{res}    242,928    .0152185    .1224212          0          1
{txt}
{com}. local bl = r(mean) 
{txt}
{com}. 
. eststo: reghdfe SCADantigov idle_index , absorb(objectid ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 242204{txt}){col 67}= {res}     11.82
{txt}{col 51}Prob > F{col 67}= {res}    0.0006
{txt}{col 51}R-squared{col 67}= {res}    0.0780
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0753
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0000
{txt}{col 51}Root MSE{col 67}= {res}    0.1177

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0031646{col 26}{space 2} .0009203{col 37}{space 1}    3.44{col 46}{space 3}0.001{col 54}{space 4} .0013608{col 67}{space 3} .0049684
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0136895{col 26}{space 2} .0004929{col 37}{space 1}   27.77{col 46}{space 3}0.000{col 54}{space 4} .0127234{col 67}{space 3} .0146556
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:20.79423492899385}"

{com}. di  ((_b[idle_index]*.35)/`bl')*100
{res}7.2779822
{txt}
{com}. //estadd local perch50 =  ((_b[idle_index]*.63)/`bl')*100
. 
. 
. *eststo: reghdfe SCADantigov idle_index , absorb(ccode) vce(r)  
. *estadd local FEcountry"x"
. *estadd local perch =  (_b[idle_index]/`bl')*100
. 
. eststo: reghdfe SCADantigov idle_index , absorb(oyfe ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 222683{txt}){col 67}= {res}     15.28
{txt}{col 51}Prob > F{col 67}= {res}    0.0001
{txt}{col 51}R-squared{col 67}= {res}    0.3268
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2656
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1049

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0031646{col 26}{space 2} .0008097{col 37}{space 1}    3.91{col 46}{space 3}0.000{col 54}{space 4} .0015776{col 67}{space 3} .0047515
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0136895{col 26}{space 2} .0004312{col 37}{space 1}   31.75{col 46}{space 3}0.000{col 54}{space 4} .0128444{col 67}{space 3} .0145346
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}        0{col 39}{result}{space 1}    20244{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est2{txt} stored)

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:20.79423492899254}"

{com}. 
. eststo: reghdfe SCADantigov idle_index , absorb(objectid oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 2 HDFE groups{col 51}F({res}   1{txt},{res} 222683{txt}){col 67}= {res}     15.28
{txt}{col 51}Prob > F{col 67}= {res}    0.0001
{txt}{col 51}R-squared{col 67}= {res}    0.3268
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2656
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1049

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0031646{col 26}{space 2} .0008097{col 37}{space 1}    3.91{col 46}{space 3}0.000{col 54}{space 4} .0015776{col 67}{space 3} .0047515
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0136895{col 26}{space 2} .0004312{col 37}{space 1}   31.75{col 46}{space 3}0.000{col 54}{space 4} .0128444{col 67}{space 3} .0145346
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:20.79423492899242}"

{com}. 
. eststo: reghdfe SCADantigov idle_index , absorb(objectid oyfe ym ) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 3 HDFE groups{col 51}F({res}   1{txt},{res} 222375{txt}){col 67}= {res}     17.87
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3279
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2658
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1049

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0034793{col 26}{space 2} .0008231{col 37}{space 1}    4.23{col 46}{space 3}0.000{col 54}{space 4}  .001866{col 67}{space 3} .0050927
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0135374{col 26}{space 2}  .000437{col 37}{space 1}   30.98{col 46}{space 3}0.000{col 54}{space 4} .0126809{col 67}{space 3}  .014394
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}          ym{col 14}{c |}{space 1}      336{col 27}{space 1}       28{col 39}{result}{space 1}      308{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est4{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:22.86261505013055}"

{com}. 
. eststo: reghdfe SCADantigov idle_index temp prec, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   241,248
{txt}Absorbing 3 HDFE groups{col 51}F({res}   3{txt},{res} 221130{txt}){col 67}= {res}      6.51
{txt}{col 51}Prob > F{col 67}= {res}    0.0002
{txt}{col 51}R-squared{col 67}= {res}    0.3273
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2661
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1051

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0028326{col 26}{space 2} .0009152{col 37}{space 1}    3.09{col 46}{space 3}0.002{col 54}{space 4} .0010388{col 67}{space 3} .0046264
{txt}{space 8}temp {c |}{col 14}{res}{space 2} .0000403{col 26}{space 2} .0000595{col 37}{space 1}    0.68{col 46}{space 3}0.498{col 54}{space 4}-.0000763{col 67}{space 3} .0001569
{txt}{space 8}prec {c |}{col 14}{res}{space 2}-4.00e-06{col 26}{space 2} 2.77e-06{col 37}{space 1}   -1.45{col 46}{space 3}0.148{col 54}{space 4}-9.43e-06{col 67}{space 3} 1.42e-06
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0132743{col 26}{space 2} .0014557{col 37}{space 1}    9.12{col 46}{space 3}0.000{col 54}{space 4} .0104211{col 67}{space 3} .0161274
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      718{col 27}{space 1}        0{col 39}{result}{space 1}      718{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20104{col 27}{space 1}      718{col 39}{result}{space 1}    19386{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est5{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:18.61264374270876}"

{com}. 
. eststo: reghdfe SCADantigov idle_index py_SCADantigov, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 3 HDFE groups{col 51}F({res}   2{txt},{res} 222671{txt}){col 67}= {res}    156.67
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3394
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2793
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0187
{txt}{col 51}Root MSE{col 67}= {res}    0.1039

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}   SCADantigov{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}idle_index {c |}{col 16}{res}{space 2} .0028637{col 28}{space 2} .0008117{col 39}{space 1}    3.53{col 48}{space 3}0.000{col 56}{space 4} .0012727{col 69}{space 3} .0044547
{txt}py_SCADantigov {c |}{col 16}{res}{space 2} .0130457{col 28}{space 2} .0007499{col 39}{space 1}   17.40{col 48}{space 3}0.000{col 56}{space 4} .0115759{col 69}{space 3} .0145155
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}-.1114918{col 28}{space 2} .0071689{col 39}{space 1}  -15.55{col 48}{space 3}0.000{col 56}{space 4}-.1255427{col 69}{space 3}-.0974408
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est6{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:18.81713188777124}"

{com}. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Table1_SCAD.csv", label nogaps compress 
> keep(idle_index)  se star(* 0.05 ** 0.01 *** 0.001) cells(b(star fmt(%9.4f)) se( fmt(%9.4f)))
> stats(perch N r2 FEobj FEoy FEcountry FEmo TP PY, fmt(%2.1f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Country-Year FE"' `"Country FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Table1_SCAD.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. 
. ** ACLED initiator ***
. 
. est clear 
{txt}
{com}. 
. *gen acled_bi = (ACLED_initiator_count>0)
. *replace acled_bi = . if ACLED_initiator_count==.
. 
. btscs acled_bi year objectid, g(py_acled_bi)
{txt}
{com}. 
. gen py2_acled  = py_acled_bi*py_acled_bi
{txt}(69,468 missing values generated)

{com}. gen py3_acled  = py_acled_bi*py_acled_bi*py_acled_bi
{txt}(69,468 missing values generated)

{com}. 
. 
. 
. sum acled_bi if sample==1 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}acled_bi {c |}{res}    182,196    .0837505     .277014          0          1
{txt}
{com}. local bl = r(mean) 
{txt}
{com}. 
. est clear
{txt}
{com}. eststo: reghdfe acled_bi idle_index , absorb(objectid ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   182,196
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 181472{txt}){col 67}= {res}     15.58
{txt}{col 51}Prob > F{col 67}= {res}    0.0001
{txt}{col 51}R-squared{col 67}= {res}    0.2185
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2154
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.2454

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}    acled_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0082934{col 26}{space 2} .0021009{col 37}{space 1}    3.95{col 46}{space 3}0.000{col 54}{space 4} .0041757{col 67}{space 3}  .012411
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0797434{col 26}{space 2} .0011526{col 37}{space 1}   69.19{col 46}{space 3}0.000{col 54}{space 4} .0774844{col 67}{space 3} .0820024
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:9.902485329336093}"

{com}. 
. eststo: reghdfe acled_bi idle_index , absorb( oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   182,196
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 167012{txt}){col 67}= {res}     21.12
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4687
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4204
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.2109

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}    acled_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0082934{col 26}{space 2} .0018044{col 37}{space 1}    4.60{col 46}{space 3}0.000{col 54}{space 4} .0047567{col 67}{space 3}   .01183
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0797434{col 26}{space 2} .0009905{col 37}{space 1}   80.51{col 46}{space 3}0.000{col 54}{space 4} .0778021{col 67}{space 3} .0816848
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15183{col 27}{space 1}        0{col 39}{result}{space 1}    15183{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est2{txt} stored)

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:9.902485329336153}"

{com}. 
. eststo: reghdfe acled_bi idle_index , absorb(objectid oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   182,196
{txt}Absorbing 2 HDFE groups{col 51}F({res}   1{txt},{res} 167012{txt}){col 67}= {res}     21.12
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4687
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4204
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.2109

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}    acled_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0082934{col 26}{space 2} .0018044{col 37}{space 1}    4.60{col 46}{space 3}0.000{col 54}{space 4} .0047567{col 67}{space 3}   .01183
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0797434{col 26}{space 2} .0009905{col 37}{space 1}   80.51{col 46}{space 3}0.000{col 54}{space 4} .0778021{col 67}{space 3} .0816848
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15183{col 27}{space 1}      723{col 39}{result}{space 1}    14460{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:9.902485329336159}"

{com}. 
. eststo: reghdfe acled_bi idle_index , absorb(objectid oyfe mon ) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   182,196
{txt}Absorbing 3 HDFE groups{col 51}F({res}   1{txt},{res} 167001{txt}){col 67}= {res}     30.23
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4688
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4205
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0002
{txt}{col 51}Root MSE{col 67}= {res}    0.2109

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}    acled_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0101406{col 26}{space 2} .0018444{col 37}{space 1}    5.50{col 46}{space 3}0.000{col 54}{space 4} .0065256{col 67}{space 3} .0137556
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0788509{col 26}{space 2} .0010078{col 37}{space 1}   78.24{col 46}{space 3}0.000{col 54}{space 4} .0768756{col 67}{space 3} .0808262
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15183{col 27}{space 1}      723{col 39}{result}{space 1}    14460{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est4{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:12.10813991824219}"

{com}. 
. eststo: reghdfe acled_bi idle_index temp prec, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   180,936
{txt}Absorbing 3 HDFE groups{col 51}F({res}   3{txt},{res} 165844{txt}){col 67}= {res}     15.39
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4699
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4216
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0003
{txt}{col 51}Root MSE{col 67}= {res}    0.2110

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}    acled_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0080691{col 26}{space 2} .0020494{col 37}{space 1}    3.94{col 46}{space 3}0.000{col 54}{space 4} .0040523{col 67}{space 3}  .012086
{txt}{space 8}temp {c |}{col 14}{res}{space 2} .0005093{col 26}{space 2} .0001386{col 37}{space 1}    3.67{col 46}{space 3}0.000{col 54}{space 4} .0002376{col 67}{space 3} .0007811
{txt}{space 8}prec {c |}{col 14}{res}{space 2}-.0000141{col 26}{space 2} 6.58e-06{col 37}{space 1}   -2.14{col 46}{space 3}0.032{col 54}{space 4} -.000027{col 67}{space 3}-1.18e-06
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0691946{col 26}{space 2} .0034349{col 37}{space 1}   20.14{col 46}{space 3}0.000{col 54}{space 4} .0624622{col 67}{space 3}  .075927
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      718{col 27}{space 1}        0{col 39}{result}{space 1}      718{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15078{col 27}{space 1}      718{col 39}{result}{space 1}    14360{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est5{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:9.634722898028223}"

{com}. 
. eststo: reghdfe acled_bi idle_index py_acled_bi, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   182,196
{txt}Absorbing 3 HDFE groups{col 51}F({res}   2{txt},{res} 167000{txt}){col 67}= {res}    277.21
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4749
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4271
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0117
{txt}{col 51}Root MSE{col 67}= {res}    0.2097

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}    acled_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0101157{col 26}{space 2} .0018307{col 37}{space 1}    5.53{col 46}{space 3}0.000{col 54}{space 4} .0065275{col 67}{space 3} .0137038
{txt}{space 1}py_acled_bi {c |}{col 14}{res}{space 2} .0260169{col 26}{space 2} .0011324{col 37}{space 1}   22.97{col 46}{space 3}0.000{col 54}{space 4} .0237973{col 67}{space 3} .0282365
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.0342539{col 26}{space 2} .0049509{col 37}{space 1}   -6.92{col 46}{space 3}0.000{col 54}{space 4}-.0439575{col 67}{space 3}-.0245503
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15183{col 27}{space 1}      723{col 39}{result}{space 1}    14460{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est6{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:12.07835374764201}"

{com}. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Table1_ACLED.csv", label nogaps compress 
> keep(idle_index)  se star(* 0.05 ** 0.01 *** 0.001) 
> stats(perch N r2 FEobj FEoy FEmo TP PY, fmt(%3.2f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Location-Year FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Table1_ACLED.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. 
. ** UCDP ***
. 
. 
. *gen UCDP_bi = (UCDP_Violent_init_count>0)
. *replace UCDP_bi = . if UCDP_Violent_init_count==.
. 
. reghdfe UCDP_bi idle_index , absorb(objectid ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 242204{txt}){col 67}= {res}      6.65
{txt}{col 51}Prob > F{col 67}= {res}    0.0099
{txt}{col 51}R-squared{col 67}= {res}    0.1741
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1716
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0000
{txt}{col 51}Root MSE{col 67}= {res}    0.1828

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0034759{col 26}{space 2} .0013477{col 37}{space 1}    2.58{col 46}{space 3}0.010{col 54}{space 4} .0008345{col 67}{space 3} .0061174
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}   .04044{col 26}{space 2} .0007432{col 37}{space 1}   54.42{col 46}{space 3}0.000{col 54}{space 4} .0389835{col 67}{space 3} .0418966
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}

{com}. gen sample_ucdp =1 if e(sample)==1
{txt}(34,944 missing values generated)

{com}. 
. btscs UCDP_bi year objectid, g(py_UCDP_bi)
{txt}
{com}. 
. gen py2_ucdp  = py_UCDP_bi*py_UCDP_bi
{txt}
{com}. gen py3_ucdp  = py_UCDP_bi*py_UCDP_bi*py_UCDP_bi
{txt}
{com}. 
. 
. 
. 
. 
. est clear 
{txt}
{com}. sum UCDP_bi if sample_ucdp==1 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}UCDP_bi {c |}{res}    242,928    .0421195    .2008621          0          1
{txt}
{com}. local bl = r(mean) 
{txt}
{com}. 
. 
. est clear
{txt}
{com}. eststo: reghdfe UCDP_bi idle_index , absorb(objectid ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 242204{txt}){col 67}= {res}      6.65
{txt}{col 51}Prob > F{col 67}= {res}    0.0099
{txt}{col 51}R-squared{col 67}= {res}    0.1741
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1716
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0000
{txt}{col 51}Root MSE{col 67}= {res}    0.1828

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0034759{col 26}{space 2} .0013477{col 37}{space 1}    2.58{col 46}{space 3}0.010{col 54}{space 4} .0008345{col 67}{space 3} .0061174
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}   .04044{col 26}{space 2} .0007432{col 37}{space 1}   54.42{col 46}{space 3}0.000{col 54}{space 4} .0389835{col 67}{space 3} .0418966
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:8.252592564223578}"

{com}. 
. eststo: reghdfe UCDP_bi idle_index , absorb( oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 222683{txt}){col 67}= {res}      9.32
{txt}{col 51}Prob > F{col 67}= {res}    0.0023
{txt}{col 51}R-squared{col 67}= {res}    0.4536
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4039
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0000
{txt}{col 51}Root MSE{col 67}= {res}    0.1551

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0034759{col 26}{space 2} .0011385{col 37}{space 1}    3.05{col 46}{space 3}0.002{col 54}{space 4} .0012446{col 67}{space 3} .0057073
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}   .04044{col 26}{space 2} .0006294{col 37}{space 1}   64.25{col 46}{space 3}0.000{col 54}{space 4} .0392063{col 67}{space 3} .0416737
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}        0{col 39}{result}{space 1}    20244{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est2{txt} stored)

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:8.25259256422463}"

{com}. 
. eststo: reghdfe UCDP_bi idle_index , absorb(objectid oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 2 HDFE groups{col 51}F({res}   1{txt},{res} 222683{txt}){col 67}= {res}      9.32
{txt}{col 51}Prob > F{col 67}= {res}    0.0023
{txt}{col 51}R-squared{col 67}= {res}    0.4536
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4039
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0000
{txt}{col 51}Root MSE{col 67}= {res}    0.1551

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0034759{col 26}{space 2} .0011385{col 37}{space 1}    3.05{col 46}{space 3}0.002{col 54}{space 4} .0012446{col 67}{space 3} .0057073
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}   .04044{col 26}{space 2} .0006294{col 37}{space 1}   64.25{col 46}{space 3}0.000{col 54}{space 4} .0392063{col 67}{space 3} .0416737
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:8.252592564224633}"

{com}. 
. eststo: reghdfe UCDP_bi idle_index , absorb(objectid oyfe mon ) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 3 HDFE groups{col 51}F({res}   1{txt},{res} 222672{txt}){col 67}= {res}      9.76
{txt}{col 51}Prob > F{col 67}= {res}    0.0018
{txt}{col 51}R-squared{col 67}= {res}    0.4539
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4043
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0000
{txt}{col 51}Root MSE{col 67}= {res}    0.1550

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0036719{col 26}{space 2} .0011756{col 37}{space 1}    3.12{col 46}{space 3}0.002{col 54}{space 4} .0013677{col 67}{space 3} .0059761
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0403454{col 26}{space 2} .0006452{col 37}{space 1}   62.53{col 46}{space 3}0.000{col 54}{space 4} .0390807{col 67}{space 3}   .04161
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est4{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:8.717780090759401}"

{com}. 
. eststo: reghdfe UCDP_bi idle_index temp prec, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   241,248
{txt}Absorbing 3 HDFE groups{col 51}F({res}   3{txt},{res} 221130{txt}){col 67}= {res}      3.60
{txt}{col 51}Prob > F{col 67}= {res}    0.0128
{txt}{col 51}R-squared{col 67}= {res}    0.4542
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4046
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0000
{txt}{col 51}Root MSE{col 67}= {res}    0.1554

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0031483{col 26}{space 2} .0012906{col 37}{space 1}    2.44{col 46}{space 3}0.015{col 54}{space 4} .0006188{col 67}{space 3} .0056779
{txt}{space 8}temp {c |}{col 14}{res}{space 2} .0000464{col 26}{space 2} .0000987{col 37}{space 1}    0.47{col 46}{space 3}0.639{col 54}{space 4}-.0001472{col 67}{space 3} .0002399
{txt}{space 8}prec {c |}{col 14}{res}{space 2}-3.93e-06{col 26}{space 2} 3.94e-06{col 37}{space 1}   -1.00{col 46}{space 3}0.318{col 54}{space 4}-.0000116{col 67}{space 3} 3.78e-06
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0400413{col 26}{space 2} .0024205{col 37}{space 1}   16.54{col 46}{space 3}0.000{col 54}{space 4} .0352971{col 67}{space 3} .0447855
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      718{col 27}{space 1}        0{col 39}{result}{space 1}      718{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20104{col 27}{space 1}      718{col 39}{result}{space 1}    19386{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est5{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:7.474738726995232}"

{com}. 
. eststo: reghdfe UCDP_bi idle_index py_UCDP_bi, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 3 HDFE groups{col 51}F({res}   2{txt},{res} 222671{txt}){col 67}= {res}    154.76
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4591
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4099
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0095
{txt}{col 51}Root MSE{col 67}= {res}    0.1543

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0036607{col 26}{space 2} .0011684{col 37}{space 1}    3.13{col 46}{space 3}0.002{col 54}{space 4} .0013707{col 67}{space 3} .0059507
{txt}{space 2}py_UCDP_bi {c |}{col 14}{res}{space 2} .0190992{col 26}{space 2}  .001102{col 37}{space 1}   17.33{col 46}{space 3}0.000{col 54}{space 4} .0169392{col 67}{space 3} .0212591
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.1240386{col 26}{space 2} .0094638{col 37}{space 1}  -13.11{col 46}{space 3}0.000{col 54}{space 4}-.1425874{col 67}{space 3}-.1054899
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est6{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:8.691180309503453}"

{com}. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Table1_UCDP.csv", label nogaps compress 
> keep(idle_index)  se star(* 0.05 ** 0.01 *** 0.001) 
> stats(perch N r2 FEobj FEoy FEmo TP PY, fmt(%3.2f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Location-Year FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Table1_UCDP.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. ***************************************************************************************
. ***************************************************************************************
. ******* Table 2: Idle index post-2000 - SCAD
. ***************************************************************************************
. ***************************************************************************************
. est clear 
{txt}
{com}. sum SCADantigov  if sample==1 &  year>2000

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}SCADantigov {c |}{res}    147,492    .0205977    .1420338          0          1
{txt}
{com}. local bl = r(mean) 
{txt}
{com}. 
. est clear
{txt}
{com}. eststo: reghdfe SCADantigov idle_index if year>2000, absorb(objectid ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   147,492
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 146768{txt}){col 67}= {res}      7.61
{txt}{col 51}Prob > F{col 67}= {res}    0.0058
{txt}{col 51}R-squared{col 67}= {res}    0.1165
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1121
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1338

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0036718{col 26}{space 2} .0013311{col 37}{space 1}    2.76{col 46}{space 3}0.006{col 54}{space 4} .0010629{col 67}{space 3} .0062807
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0188237{col 26}{space 2} .0007176{col 37}{space 1}   26.23{col 46}{space 3}0.000{col 54}{space 4} .0174171{col 67}{space 3} .0202302
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:17.82627383410553}"

{com}. 
. eststo: reghdfe SCADantigov idle_index  if year>2000, absorb( oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   147,492
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 135200{txt}){col 67}= {res}      9.53
{txt}{col 51}Prob > F{col 67}= {res}    0.0020
{txt}{col 51}R-squared{col 67}= {res}    0.3391
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2791
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1206

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0036718{col 26}{space 2} .0011894{col 37}{space 1}    3.09{col 46}{space 3}0.002{col 54}{space 4} .0013406{col 67}{space 3}  .006003
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0188237{col 26}{space 2} .0006364{col 37}{space 1}   29.58{col 46}{space 3}0.000{col 54}{space 4} .0175763{col 67}{space 3}  .020071
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    12291{col 27}{space 1}        0{col 39}{result}{space 1}    12291{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est2{txt} stored)

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:17.82627383410642}"

{com}. 
. eststo: reghdfe SCADantigov idle_index  if year>2000, absorb(objectid oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   147,492
{txt}Absorbing 2 HDFE groups{col 51}F({res}   1{txt},{res} 135200{txt}){col 67}= {res}      9.53
{txt}{col 51}Prob > F{col 67}= {res}    0.0020
{txt}{col 51}R-squared{col 67}= {res}    0.3391
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2791
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1206

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0036718{col 26}{space 2} .0011894{col 37}{space 1}    3.09{col 46}{space 3}0.002{col 54}{space 4} .0013406{col 67}{space 3}  .006003
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0188237{col 26}{space 2} .0006364{col 37}{space 1}   29.58{col 46}{space 3}0.000{col 54}{space 4} .0175763{col 67}{space 3}  .020071
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    12291{col 27}{space 1}      723{col 39}{result}{space 1}    11568{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:17.82627383410644}"

{com}. 
. eststo: reghdfe SCADantigov idle_index  if year>2000, absorb(objectid oyfe mon ) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   147,492
{txt}Absorbing 3 HDFE groups{col 51}F({res}   1{txt},{res} 135189{txt}){col 67}= {res}     12.85
{txt}{col 51}Prob > F{col 67}= {res}    0.0003
{txt}{col 51}R-squared{col 67}= {res}    0.3393
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2792
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1206

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0043141{col 26}{space 2} .0012033{col 37}{space 1}    3.59{col 46}{space 3}0.000{col 54}{space 4} .0019557{col 67}{space 3} .0066726
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0185133{col 26}{space 2} .0006418{col 37}{space 1}   28.85{col 46}{space 3}0.000{col 54}{space 4} .0172555{col 67}{space 3} .0197711
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    12291{col 27}{space 1}      723{col 39}{result}{space 1}    11568{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est4{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:20.94475782516877}"

{com}. 
. eststo: reghdfe SCADantigov idle_index temp prec  if year>2000, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   146,472
{txt}Absorbing 3 HDFE groups{col 51}F({res}   3{txt},{res} 134252{txt}){col 67}= {res}      4.31
{txt}{col 51}Prob > F{col 67}= {res}    0.0048
{txt}{col 51}R-squared{col 67}= {res}    0.3397
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2796
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1208

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0037775{col 26}{space 2}   .00134{col 37}{space 1}    2.82{col 46}{space 3}0.005{col 54}{space 4} .0011511{col 67}{space 3}  .006404
{txt}{space 8}temp {c |}{col 14}{res}{space 2}-.0000173{col 26}{space 2} .0000862{col 37}{space 1}   -0.20{col 46}{space 3}0.841{col 54}{space 4}-.0001863{col 67}{space 3} .0001516
{txt}{space 8}prec {c |}{col 14}{res}{space 2}-3.28e-06{col 26}{space 2} 4.12e-06{col 37}{space 1}   -0.80{col 46}{space 3}0.426{col 54}{space 4}-.0000114{col 67}{space 3} 4.79e-06
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0195304{col 26}{space 2} .0021329{col 37}{space 1}    9.16{col 46}{space 3}0.000{col 54}{space 4} .0153499{col 67}{space 3} .0237108
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      718{col 27}{space 1}        0{col 39}{result}{space 1}      718{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    12206{col 27}{space 1}      718{col 39}{result}{space 1}    11488{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est5{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:18.33962019216997}"

{com}. 
. eststo: reghdfe SCADantigov idle_index py_SCADantigov  if year>2000, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   147,492
{txt}Absorbing 3 HDFE groups{col 51}F({res}   2{txt},{res} 135188{txt}){col 67}= {res}    122.64
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3512
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2922
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0181
{txt}{col 51}Root MSE{col 67}= {res}    0.1195

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}   SCADantigov{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}idle_index {c |}{col 16}{res}{space 2}  .003515{col 28}{space 2} .0011886{col 39}{space 1}    2.96{col 48}{space 3}0.003{col 56}{space 4} .0011854{col 69}{space 3} .0058446
{txt}py_SCADantigov {c |}{col 16}{res}{space 2} .0118066{col 28}{space 2}  .000767{col 39}{space 1}   15.39{col 48}{space 3}0.000{col 56}{space 4} .0103034{col 69}{space 3} .0133099
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}-.1342425{col 28}{space 2} .0098922{col 39}{space 1}  -13.57{col 48}{space 3}0.000{col 56}{space 4}-.1536311{col 69}{space 3}-.1148539
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    12291{col 27}{space 1}      723{col 39}{result}{space 1}    11568{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est6{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:17.06491394642731}"

{com}. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Table2_POST2000.csv", label nogaps compress 
> keep(idle_index)  se star(* 0.05 ** 0.01 *** 0.001)  cells(b(star fmt(%9.4f)) se( fmt(%9.4f)))
> stats(perch N r2 FEobj FEoy FEmo TP PY, fmt(%3.2f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Location-Year FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Table2_POST2000.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. 
. ***************************************************************************************
. ***************************************************************************************
. ****** Figure 3: Constrained sample by year
. ***************************************************************************************
. ***************************************************************************************
. 
. est clear 
{txt}
{com}. sum SCADantigov  if sample==1 &  year>2000

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}SCADantigov {c |}{res}    147,492    .0205977    .1420338          0          1
{txt}
{com}. local bl = r(mean) 
{txt}
{com}. 
. cap drop y_* sim_year
{txt}
{com}. gen y_coef =.
{txt}(277,872 missing values generated)

{com}. gen y_ub=.
{txt}(277,872 missing values generated)

{com}. gen y_lb =. 
{txt}(277,872 missing values generated)

{com}. gen sim_year = .
{txt}(277,872 missing values generated)

{com}. forval i = 1990/2010{c -(}
{txt}  2{com}. qui reghdfe SCADantigov idle_index if year>`i', absorb(objectid oyfe mon) vce(r)  
{txt}  3{com}. replace y_coef = _b[idle_index] if _n==`i'
{txt}  4{com}. replace y_ub = _b[idle_index] + (1.96 * _se[idle_index]) if _n==`i'
{txt}  5{com}. replace y_lb = _b[idle_index] - (1.96 * _se[idle_index]) if _n==`i'
{txt}  6{com}. replace sim_year=`i' if _n==`i'
{txt}  7{com}. {c )-}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)

{com}. 
. #delimit ; 
{txt}delimiter now ;
{com}. twoway  (rcap y_ub y_lb sim_year, sort msize(medium) lcolor(blue)) 
>                 (scatter y_coef sim_year, mcolor(red)), 
>                 scheme(s1mono) yline(0) legend(off) 
>                 xtitle("Year Constraint") ytitle("Coef. Idle Index");
{res}{txt}
{com}. #delimit cr
{txt}delimiter now cr
{com}. graph export "FigTbl/Fig3_yearconst.png", replace
{txt}(file FigTbl/Fig3_yearconst.png written in PNG format)

{com}. 
. ***************************************************************************************
. ***************************************************************************************
. ***************************************************************************************
. ***************************************************************************************
. **** Figure 4: The marginal effect of idleness across the log of the percentage of cultivated land.
. **** Table A4: Conditional Relationship across the log of % of cultivated land 
. ***************************************************************************************
. ***************************************************************************************
. ***************************************************************************************
. ***************************************************************************************
. 
. est clear
{txt}
{com}. cap drop X
{txt}
{com}. cap gen lncult = ln(cultivated+1)
{txt}
{com}. lab var lncult "log of % Cultivated Land"
{txt}
{com}. gen X = lncult*idle_index
{txt}(34,944 missing values generated)

{com}. lab var X "idle X log of % Cultivated Land"
{txt}
{com}. 
. eststo: reghdfe SCADantigov idle_index lncult X, absorb( objectid oyfe mon ) vce(r)  
{res}{txt}note: {res}lncult{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}{txt}note: lncult omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 3 HDFE groups{col 51}F({res}   2{txt},{res} 222671{txt}){col 67}= {res}     10.22
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3269
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2656
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1049

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2}-.0022392{col 26}{space 2} .0034779{col 37}{space 1}   -0.64{col 46}{space 3}0.520{col 54}{space 4}-.0090558{col 67}{space 3} .0045774
{txt}{space 6}lncult {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 11}X {c |}{col 14}{res}{space 2} .0015675{col 26}{space 2} .0009305{col 37}{space 1}    1.68{col 46}{space 3}0.092{col 54}{space 4}-.0002563{col 67}{space 3} .0033913
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0136653{col 26}{space 2} .0004426{col 37}{space 1}   30.88{col 46}{space 3}0.000{col 54}{space 4} .0127979{col 67}{space 3} .0145328
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. 
. grinter idle_index, inter(X) const02(lncult) scheme(s1mono) kdensity yline(0) 
{res}{txt}
{com}. graph export "FigTbl/Fig4_mfx_cultivated.pdf", replace
{txt}(file FigTbl/Fig4_mfx_cultivated.pdf written in PDF format)

{com}. 
. 
. eststo: reghdfe SCADantigov idle_index lncult X temp prec, absorb( objectid oyfe mon ) vce(r)  
{res}{txt}note: {res}lncult{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}{txt}note: lncult omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   241,248
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res} 221129{txt}){col 67}= {res}      5.59
{txt}{col 51}Prob > F{col 67}= {res}    0.0002
{txt}{col 51}R-squared{col 67}= {res}    0.3273
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2661
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1051

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2}-.0033453{col 26}{space 2} .0037146{col 37}{space 1}   -0.90{col 46}{space 3}0.368{col 54}{space 4}-.0106259{col 67}{space 3} .0039352
{txt}{space 6}lncult {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 11}X {c |}{col 14}{res}{space 2} .0016908{col 26}{space 2} .0009896{col 37}{space 1}    1.71{col 46}{space 3}0.088{col 54}{space 4}-.0002488{col 67}{space 3} .0036304
{txt}{space 8}temp {c |}{col 14}{res}{space 2} .0000293{col 26}{space 2}   .00006{col 37}{space 1}    0.49{col 46}{space 3}0.625{col 54}{space 4}-.0000883{col 67}{space 3} .0001468
{txt}{space 8}prec {c |}{col 14}{res}{space 2}-3.98e-06{col 26}{space 2} 2.77e-06{col 37}{space 1}   -1.44{col 46}{space 3}0.150{col 54}{space 4}-9.41e-06{col 67}{space 3} 1.45e-06
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0136561{col 26}{space 2} .0014757{col 37}{space 1}    9.25{col 46}{space 3}0.000{col 54}{space 4} .0107638{col 67}{space 3} .0165483
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      718{col 27}{space 1}        0{col 39}{result}{space 1}      718{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20104{col 27}{space 1}      718{col 39}{result}{space 1}    19386{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est2{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. 
. 
. eststo: reghdfe SCADantigov idle_index lncult X py_SCADantigov, absorb( objectid oyfe mon ) vce(r)  
{res}{txt}note: {res}lncult{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}{txt}note: lncult omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 3 HDFE groups{col 51}F({res}   3{txt},{res} 222670{txt}){col 67}= {res}    105.21
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3394
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2793
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0187
{txt}{col 51}Root MSE{col 67}= {res}    0.1039

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}   SCADantigov{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}idle_index {c |}{col 16}{res}{space 2}-.0029463{col 28}{space 2} .0034452{col 39}{space 1}   -0.86{col 48}{space 3}0.392{col 56}{space 4}-.0096988{col 69}{space 3} .0038062
{txt}{space 8}lncult {c |}{col 16}{res}{space 2}        0{col 28}{txt}  (omitted)
{space 13}X {c |}{col 16}{res}{space 2} .0015926{col 28}{space 2} .0009227{col 39}{space 1}    1.73{col 48}{space 3}0.084{col 56}{space 4}-.0002159{col 69}{space 3}  .003401
{txt}py_SCADantigov {c |}{col 16}{res}{space 2} .0130459{col 28}{space 2} .0007499{col 39}{space 1}   17.40{col 48}{space 3}0.000{col 56}{space 4} .0115761{col 69}{space 3} .0145157
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}-.1113633{col 28}{space 2} .0071688{col 39}{space 1}  -15.53{col 48}{space 3}0.000{col 56}{space 4}-.1254139{col 69}{space 3}-.0973126
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. 
. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Appendix_TblA4_cond.csv", label nogaps compress 
> keep(idle_index X)  se star(* 0.05 ** 0.01 *** 0.001) 
> stats(perch N r2 FEobj FEoy FEcountry FEmo TP PY, fmt(%3.2f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Location-Year FE"' `"Country FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Appendix_TblA4_cond.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. 
. ******************************************************************************************************************************************************
. ******************************************************************************************************************************************************
. ******************************************************************************************************************************************************
. ******************************************************************************************************************************************************
. ** APPENDIX TABLES AND FIGURES
. ******************************************************************************************************************************************************
. ******************************************************************************************************************************************************
. ******************************************************************************************************************************************************
. ******************************************************************************************************************************************************
. 
. 
. 
. ***************************************************************************************
. ***************************************************************************************
. ****** Table A1: Logit Models
. ***************************************************************************************
. ***************************************************************************************
. 
. set matsize 10000
{txt}
{com}. 
. xtset objectid ym
{res}{txt}{col 8}panel variable:  {res}objectid (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}ym, 360 to 695
{txt}{col 17}delta:  {res}1 unit
{txt}
{com}. 
. 
. est clear
{txt}
{com}. eststo:  xtlogit SCADantigov idle_index, fe 
{txt}note: multiple positive outcomes within groups encountered.
note: 297 groups (99,792 obs) dropped because of all positive or
      all negative outcomes.
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-13563.858}  
Iteration 1:{space 3}log likelihood = {res: -13551.86}  
Iteration 2:{space 3}log likelihood = {res: -13551.85}  
Iteration 3:{space 3}log likelihood = {res: -13551.85}  
{res}
{txt}Conditional fixed-effects logistic regression{col 49}Number of obs{col 67}={col 69}{res}   143,136
{txt}Group variable: {res}objectid{col 49}{txt}Number of groups{col 67}={col 69}{res}       426

{txt}{col 49}Obs per group:
{col 63}min{col 67}={col 69}{res}       336
{txt}{col 63}avg{col 67}={col 69}{res}     336.0
{txt}{col 63}max{col 67}={col 69}{res}       336

{txt}{col 49}LR chi2({res}1{txt}){col 67}={col 70}{res}    12.08
{txt}Log likelihood  = {res} -13551.85{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0005

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .2266201{col 26}{space 2} .0648396{col 37}{space 1}    3.50{col 46}{space 3}0.000{col 54}{space 4} .0995368{col 67}{space 3} .3537033
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. 
. eststo:  xtlogit SCADantigov i.year idle_index temp prec py_SCADantigov, fe
{txt}note: multiple positive outcomes within groups encountered.
note: 295 groups (99,120 obs) dropped because of all positive or
      all negative outcomes.
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-12191.846}  
Iteration 1:{space 3}log likelihood = {res:-12032.666}  
Iteration 2:{space 3}log likelihood = {res: -12008.39}  
Iteration 3:{space 3}log likelihood = {res:-12008.378}  
Iteration 4:{space 3}log likelihood = {res:-12008.378}  
{res}
{txt}Conditional fixed-effects logistic regression{col 49}Number of obs{col 67}={col 69}{res}   142,128
{txt}Group variable: {res}objectid{col 49}{txt}Number of groups{col 67}={col 69}{res}       423

{txt}{col 49}Obs per group:
{col 63}min{col 67}={col 69}{res}       336
{txt}{col 63}avg{col 67}={col 69}{res}     336.0
{txt}{col 63}max{col 67}={col 69}{res}       336

{txt}{col 49}LR chi2({res}31{txt}){col 67}={col 70}{res}  3005.70
{txt}Log likelihood  = {res}-12008.378{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   SCADantigov{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      z{col 48}   P>|z|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}year {c |}
{space 9}1991  {c |}{col 16}{res}{space 2}  .761623{col 28}{space 2} .2402579{col 39}{space 1}    3.17{col 48}{space 3}0.002{col 56}{space 4} .2907262{col 69}{space 3}  1.23252
{txt}{space 9}1992  {c |}{col 16}{res}{space 2}  .980466{col 28}{space 2} .2349855{col 39}{space 1}    4.17{col 48}{space 3}0.000{col 56}{space 4} .5199029{col 69}{space 3} 1.441029
{txt}{space 9}1993  {c |}{col 16}{res}{space 2} .9650901{col 28}{space 2} .2383738{col 39}{space 1}    4.05{col 48}{space 3}0.000{col 56}{space 4}  .497886{col 69}{space 3} 1.432294
{txt}{space 9}1994  {c |}{col 16}{res}{space 2} .9385276{col 28}{space 2} .2416821{col 39}{space 1}    3.88{col 48}{space 3}0.000{col 56}{space 4} .4648394{col 69}{space 3} 1.412216
{txt}{space 9}1995  {c |}{col 16}{res}{space 2} .8904142{col 28}{space 2} .2463263{col 39}{space 1}    3.61{col 48}{space 3}0.000{col 56}{space 4} .4076234{col 69}{space 3} 1.373205
{txt}{space 9}1996  {c |}{col 16}{res}{space 2} 1.455214{col 28}{space 2} .2279385{col 39}{space 1}    6.38{col 48}{space 3}0.000{col 56}{space 4} 1.008463{col 69}{space 3} 1.901966
{txt}{space 9}1997  {c |}{col 16}{res}{space 2} 1.304737{col 28}{space 2} .2327735{col 39}{space 1}    5.61{col 48}{space 3}0.000{col 56}{space 4} .8485089{col 69}{space 3} 1.760964
{txt}{space 9}1998  {c |}{col 16}{res}{space 2} 1.561003{col 28}{space 2}  .226143{col 39}{space 1}    6.90{col 48}{space 3}0.000{col 56}{space 4} 1.117771{col 69}{space 3} 2.004235
{txt}{space 9}1999  {c |}{col 16}{res}{space 2} 1.513301{col 28}{space 2} .2283955{col 39}{space 1}    6.63{col 48}{space 3}0.000{col 56}{space 4} 1.065654{col 69}{space 3} 1.960948
{txt}{space 9}2000  {c |}{col 16}{res}{space 2}  1.31775{col 28}{space 2} .2347591{col 39}{space 1}    5.61{col 48}{space 3}0.000{col 56}{space 4} .8576302{col 69}{space 3} 1.777869
{txt}{space 9}2001  {c |}{col 16}{res}{space 2} 1.090691{col 28}{space 2} .2444399{col 39}{space 1}    4.46{col 48}{space 3}0.000{col 56}{space 4}  .611598{col 69}{space 3} 1.569785
{txt}{space 9}2002  {c |}{col 16}{res}{space 2} 1.569136{col 28}{space 2} .2296326{col 39}{space 1}    6.83{col 48}{space 3}0.000{col 56}{space 4} 1.119064{col 69}{space 3} 2.019207
{txt}{space 9}2003  {c |}{col 16}{res}{space 2}  1.24604{col 28}{space 2} .2409379{col 39}{space 1}    5.17{col 48}{space 3}0.000{col 56}{space 4} .7738098{col 69}{space 3} 1.718269
{txt}{space 9}2004  {c |}{col 16}{res}{space 2} 1.419918{col 28}{space 2} .2353803{col 39}{space 1}    6.03{col 48}{space 3}0.000{col 56}{space 4} .9585807{col 69}{space 3} 1.881255
{txt}{space 9}2005  {c |}{col 16}{res}{space 2}  1.69736{col 28}{space 2} .2274212{col 39}{space 1}    7.46{col 48}{space 3}0.000{col 56}{space 4} 1.251622{col 69}{space 3} 2.143097
{txt}{space 9}2006  {c |}{col 16}{res}{space 2} 1.841932{col 28}{space 2} .2240006{col 39}{space 1}    8.22{col 48}{space 3}0.000{col 56}{space 4} 1.402899{col 69}{space 3} 2.280965
{txt}{space 9}2007  {c |}{col 16}{res}{space 2} 1.603753{col 28}{space 2} .2295361{col 39}{space 1}    6.99{col 48}{space 3}0.000{col 56}{space 4} 1.153871{col 69}{space 3} 2.053635
{txt}{space 9}2008  {c |}{col 16}{res}{space 2} 1.918718{col 28}{space 2} .2222154{col 39}{space 1}    8.63{col 48}{space 3}0.000{col 56}{space 4} 1.483184{col 69}{space 3} 2.354252
{txt}{space 9}2009  {c |}{col 16}{res}{space 2}  1.81518{col 28}{space 2} .2244704{col 39}{space 1}    8.09{col 48}{space 3}0.000{col 56}{space 4} 1.375226{col 69}{space 3} 2.255134
{txt}{space 9}2010  {c |}{col 16}{res}{space 2}  2.14489{col 28}{space 2} .2173991{col 39}{space 1}    9.87{col 48}{space 3}0.000{col 56}{space 4} 1.718796{col 69}{space 3} 2.570985
{txt}{space 9}2011  {c |}{col 16}{res}{space 2} 2.480281{col 28}{space 2}  .211603{col 39}{space 1}   11.72{col 48}{space 3}0.000{col 56}{space 4} 2.065546{col 69}{space 3} 2.895015
{txt}{space 9}2012  {c |}{col 16}{res}{space 2} 2.711442{col 28}{space 2} .2075628{col 39}{space 1}   13.06{col 48}{space 3}0.000{col 56}{space 4} 2.304627{col 69}{space 3} 3.118258
{txt}{space 9}2013  {c |}{col 16}{res}{space 2} 3.056888{col 28}{space 2}  .204103{col 39}{space 1}   14.98{col 48}{space 3}0.000{col 56}{space 4} 2.656854{col 69}{space 3} 3.456923
{txt}{space 9}2014  {c |}{col 16}{res}{space 2} 3.102113{col 28}{space 2} .2033669{col 39}{space 1}   15.25{col 48}{space 3}0.000{col 56}{space 4} 2.703521{col 69}{space 3} 3.500705
{txt}{space 9}2015  {c |}{col 16}{res}{space 2} 3.151321{col 28}{space 2} .2029247{col 39}{space 1}   15.53{col 48}{space 3}0.000{col 56}{space 4} 2.753596{col 69}{space 3} 3.549046
{txt}{space 9}2016  {c |}{col 16}{res}{space 2} 2.874084{col 28}{space 2} .2044139{col 39}{space 1}   14.06{col 48}{space 3}0.000{col 56}{space 4}  2.47344{col 69}{space 3} 3.274728
{txt}{space 9}2017  {c |}{col 16}{res}{space 2}  3.00151{col 28}{space 2} .2034734{col 39}{space 1}   14.75{col 48}{space 3}0.000{col 56}{space 4}  2.60271{col 69}{space 3} 3.400311
{txt}{space 14} {c |}
{space 4}idle_index {c |}{col 16}{res}{space 2} .1978263{col 28}{space 2}  .074663{col 39}{space 1}    2.65{col 48}{space 3}0.008{col 56}{space 4} .0514894{col 69}{space 3} .3441631
{txt}{space 10}temp {c |}{col 16}{res}{space 2} .0023019{col 28}{space 2} .0053621{col 39}{space 1}    0.43{col 48}{space 3}0.668{col 56}{space 4}-.0082076{col 69}{space 3} .0128115
{txt}{space 10}prec {c |}{col 16}{res}{space 2}-.0005309{col 28}{space 2} .0002819{col 39}{space 1}   -1.88{col 48}{space 3}0.060{col 56}{space 4}-.0010833{col 69}{space 3} .0000215
{txt}py_SCADantigov {c |}{col 16}{res}{space 2}-.0926648{col 28}{space 2} .0049673{col 39}{space 1}  -18.66{col 48}{space 3}0.000{col 56}{space 4}-.1024005{col 69}{space 3}-.0829291
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est2{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. 
.  
. eststo:  xtlogit acled_bi idle_index, fe 
{txt}note: multiple positive outcomes within groups encountered.
note: 121 groups (30,492 obs) dropped because of all positive or
      all negative outcomes.
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-36392.292}  
Iteration 1:{space 3}log likelihood = {res: -36334.16}  
Iteration 2:{space 3}log likelihood = {res:-36334.078}  
Iteration 3:{space 3}log likelihood = {res:-36334.078}  
{res}
{txt}Conditional fixed-effects logistic regression{col 49}Number of obs{col 67}={col 69}{res}   151,704
{txt}Group variable: {res}objectid{col 49}{txt}Number of groups{col 67}={col 69}{res}       602

{txt}{col 49}Obs per group:
{col 63}min{col 67}={col 69}{res}       252
{txt}{col 63}avg{col 67}={col 69}{res}     252.0
{txt}{col 63}max{col 67}={col 69}{res}       252

{txt}{col 49}LR chi2({res}1{txt}){col 67}={col 70}{res}    15.62
{txt}Log likelihood  = {res}-36334.078{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0001

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    acled_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .1494277{col 26}{space 2} .0376757{col 37}{space 1}    3.97{col 46}{space 3}0.000{col 54}{space 4} .0755847{col 67}{space 3} .2232707
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. 
. eststo:  xtlogit acled_bi i.year idle_index temp prec py_acled_bi, fe
{txt}note: multiple positive outcomes within groups encountered.
note: 121 groups (30,492 obs) dropped because of all positive or
      all negative outcomes.
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-34077.289}  
Iteration 1:{space 3}log likelihood = {res:-33626.107}  
Iteration 2:{space 3}log likelihood = {res:-33336.798}  
Iteration 3:{space 3}log likelihood = {res:-33336.502}  
Iteration 4:{space 3}log likelihood = {res:-33336.502}  
{res}
{txt}Conditional fixed-effects logistic regression{col 49}Number of obs{col 67}={col 69}{res}   150,444
{txt}Group variable: {res}objectid{col 49}{txt}Number of groups{col 67}={col 69}{res}       597

{txt}{col 49}Obs per group:
{col 63}min{col 67}={col 69}{res}       252
{txt}{col 63}avg{col 67}={col 69}{res}     252.0
{txt}{col 63}max{col 67}={col 69}{res}       252

{txt}{col 49}LR chi2({res}24{txt}){col 67}={col 70}{res}  5618.13
{txt}Log likelihood  = {res}-33336.502{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    acled_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}year {c |}
{space 7}1998  {c |}{col 14}{res}{space 2} .2989089{col 26}{space 2} .0709571{col 37}{space 1}    4.21{col 46}{space 3}0.000{col 54}{space 4} .1598355{col 67}{space 3} .4379824
{txt}{space 7}1999  {c |}{col 14}{res}{space 2} .6671647{col 26}{space 2} .0687365{col 37}{space 1}    9.71{col 46}{space 3}0.000{col 54}{space 4} .5324436{col 67}{space 3} .8018858
{txt}{space 7}2000  {c |}{col 14}{res}{space 2} .7708097{col 26}{space 2} .0685455{col 37}{space 1}   11.25{col 46}{space 3}0.000{col 54}{space 4} .6364631{col 67}{space 3} .9051563
{txt}{space 7}2001  {c |}{col 14}{res}{space 2} .6388309{col 26}{space 2} .0705814{col 37}{space 1}    9.05{col 46}{space 3}0.000{col 54}{space 4}  .500494{col 67}{space 3} .7771679
{txt}{space 7}2002  {c |}{col 14}{res}{space 2} .7437522{col 26}{space 2} .0698212{col 37}{space 1}   10.65{col 46}{space 3}0.000{col 54}{space 4} .6069052{col 67}{space 3} .8805993
{txt}{space 7}2003  {c |}{col 14}{res}{space 2} .5572664{col 26}{space 2} .0722802{col 37}{space 1}    7.71{col 46}{space 3}0.000{col 54}{space 4} .4155997{col 67}{space 3}  .698933
{txt}{space 7}2004  {c |}{col 14}{res}{space 2} .4718942{col 26}{space 2} .0741723{col 37}{space 1}    6.36{col 46}{space 3}0.000{col 54}{space 4} .3265191{col 67}{space 3} .6172693
{txt}{space 7}2005  {c |}{col 14}{res}{space 2} .4169463{col 26}{space 2} .0754918{col 37}{space 1}    5.52{col 46}{space 3}0.000{col 54}{space 4} .2689852{col 67}{space 3} .5649075
{txt}{space 7}2006  {c |}{col 14}{res}{space 2} .6613667{col 26}{space 2} .0735415{col 37}{space 1}    8.99{col 46}{space 3}0.000{col 54}{space 4}  .517228{col 67}{space 3} .8055054
{txt}{space 7}2007  {c |}{col 14}{res}{space 2} .7253018{col 26}{space 2} .0730308{col 37}{space 1}    9.93{col 46}{space 3}0.000{col 54}{space 4}  .582164{col 67}{space 3} .8684396
{txt}{space 7}2008  {c |}{col 14}{res}{space 2} .8552476{col 26}{space 2} .0714577{col 37}{space 1}   11.97{col 46}{space 3}0.000{col 54}{space 4}  .715193{col 67}{space 3} .9953022
{txt}{space 7}2009  {c |}{col 14}{res}{space 2} .6699493{col 26}{space 2} .0727196{col 37}{space 1}    9.21{col 46}{space 3}0.000{col 54}{space 4} .5274215{col 67}{space 3} .8124772
{txt}{space 7}2010  {c |}{col 14}{res}{space 2} .7683957{col 26}{space 2} .0718004{col 37}{space 1}   10.70{col 46}{space 3}0.000{col 54}{space 4} .6276694{col 67}{space 3}  .909122
{txt}{space 7}2011  {c |}{col 14}{res}{space 2} .9461481{col 26}{space 2} .0689959{col 37}{space 1}   13.71{col 46}{space 3}0.000{col 54}{space 4} .8109185{col 67}{space 3} 1.081378
{txt}{space 7}2012  {c |}{col 14}{res}{space 2} 1.187247{col 26}{space 2} .0667461{col 37}{space 1}   17.79{col 46}{space 3}0.000{col 54}{space 4} 1.056427{col 67}{space 3} 1.318067
{txt}{space 7}2013  {c |}{col 14}{res}{space 2}   1.4714{col 26}{space 2} .0648159{col 37}{space 1}   22.70{col 46}{space 3}0.000{col 54}{space 4} 1.344363{col 67}{space 3} 1.598437
{txt}{space 7}2014  {c |}{col 14}{res}{space 2} 1.642497{col 26}{space 2} .0638796{col 37}{space 1}   25.71{col 46}{space 3}0.000{col 54}{space 4} 1.517295{col 67}{space 3} 1.767699
{txt}{space 7}2015  {c |}{col 14}{res}{space 2} 1.652628{col 26}{space 2} .0636358{col 37}{space 1}   25.97{col 46}{space 3}0.000{col 54}{space 4} 1.527904{col 67}{space 3} 1.777352
{txt}{space 7}2016  {c |}{col 14}{res}{space 2} 1.531342{col 26}{space 2} .0639516{col 37}{space 1}   23.95{col 46}{space 3}0.000{col 54}{space 4} 1.405999{col 67}{space 3} 1.656685
{txt}{space 7}2017  {c |}{col 14}{res}{space 2} 1.694917{col 26}{space 2} .0631691{col 37}{space 1}   26.83{col 46}{space 3}0.000{col 54}{space 4} 1.571108{col 67}{space 3} 1.818726
{txt}{space 12} {c |}
{space 2}idle_index {c |}{col 14}{res}{space 2} .1226149{col 26}{space 2} .0430122{col 37}{space 1}    2.85{col 46}{space 3}0.004{col 54}{space 4} .0383126{col 67}{space 3} .2069172
{txt}{space 8}temp {c |}{col 14}{res}{space 2} .0114804{col 26}{space 2} .0029688{col 37}{space 1}    3.87{col 46}{space 3}0.000{col 54}{space 4} .0056617{col 67}{space 3} .0172992
{txt}{space 8}prec {c |}{col 14}{res}{space 2}-.0002804{col 26}{space 2} .0001449{col 37}{space 1}   -1.94{col 46}{space 3}0.053{col 54}{space 4}-.0005644{col 67}{space 3} 3.58e-06
{txt}{space 1}py_acled_bi {c |}{col 14}{res}{space 2}-.3117292{col 26}{space 2} .0073189{col 37}{space 1}  -42.59{col 46}{space 3}0.000{col 54}{space 4} -.326074{col 67}{space 3}-.2973844
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est4{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. 
. 
. eststo:  xtlogit UCDP_bi idle_index, fe 
{txt}note: multiple positive outcomes within groups encountered.
note: 307 groups (103,152 obs) dropped because of all positive or
      all negative outcomes.
{res}
{txt}Iteration 0:{space 3}log likelihood = {res: -28005.14}  
Iteration 1:{space 3}log likelihood = {res:-27987.849}  
Iteration 2:{space 3}log likelihood = {res:-27987.837}  
Iteration 3:{space 3}log likelihood = {res:-27987.837}  
{res}
{txt}Conditional fixed-effects logistic regression{col 49}Number of obs{col 67}={col 69}{res}   139,776
{txt}Group variable: {res}objectid{col 49}{txt}Number of groups{col 67}={col 69}{res}       416

{txt}{col 49}Obs per group:
{col 63}min{col 67}={col 69}{res}       336
{txt}{col 63}avg{col 67}={col 69}{res}     336.0
{txt}{col 63}max{col 67}={col 69}{res}       336

{txt}{col 49}LR chi2({res}1{txt}){col 67}={col 70}{res}     6.64
{txt}Log likelihood  = {res}-27987.837{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0100

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .1137008{col 26}{space 2} .0439793{col 37}{space 1}    2.59{col 46}{space 3}0.010{col 54}{space 4}  .027503{col 67}{space 3} .1998985
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est5{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. 
. eststo:  xtlogit UCDP_bi i.year idle_index temp prec py_UCDP_bi, fe
{txt}note: multiple positive outcomes within groups encountered.
note: 305 groups (102,480 obs) dropped because of all positive or
      all negative outcomes.
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-25197.599}  
Iteration 1:{space 3}log likelihood = {res:-24951.349}  
Iteration 2:{space 3}log likelihood = {res:-24888.013}  
Iteration 3:{space 3}log likelihood = {res:-24887.757}  
Iteration 4:{space 3}log likelihood = {res:-24887.757}  
{res}
{txt}Conditional fixed-effects logistic regression{col 49}Number of obs{col 67}={col 69}{res}   138,768
{txt}Group variable: {res}objectid{col 49}{txt}Number of groups{col 67}={col 69}{res}       413

{txt}{col 49}Obs per group:
{col 63}min{col 67}={col 69}{res}       336
{txt}{col 63}avg{col 67}={col 69}{res}     336.0
{txt}{col 63}max{col 67}={col 69}{res}       336

{txt}{col 49}LR chi2({res}31{txt}){col 67}={col 70}{res}  6076.14
{txt}Log likelihood  = {res}-24887.757{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}year {c |}
{space 7}1991  {c |}{col 14}{res}{space 2}-.1268642{col 26}{space 2} .0995642{col 37}{space 1}   -1.27{col 46}{space 3}0.203{col 54}{space 4}-.3220063{col 67}{space 3}  .068278
{txt}{space 7}1992  {c |}{col 14}{res}{space 2} .2751543{col 26}{space 2} .0946892{col 37}{space 1}    2.91{col 46}{space 3}0.004{col 54}{space 4} .0895669{col 67}{space 3} .4607416
{txt}{space 7}1993  {c |}{col 14}{res}{space 2} .8166023{col 26}{space 2}  .087979{col 37}{space 1}    9.28{col 46}{space 3}0.000{col 54}{space 4} .6441666{col 67}{space 3}  .989038
{txt}{space 7}1994  {c |}{col 14}{res}{space 2} 1.145848{col 26}{space 2} .0854929{col 37}{space 1}   13.40{col 46}{space 3}0.000{col 54}{space 4}  .978285{col 67}{space 3} 1.313411
{txt}{space 7}1995  {c |}{col 14}{res}{space 2} 1.123715{col 26}{space 2} .0865619{col 37}{space 1}   12.98{col 46}{space 3}0.000{col 54}{space 4} .9540567{col 67}{space 3} 1.293373
{txt}{space 7}1996  {c |}{col 14}{res}{space 2} .6025917{col 26}{space 2} .0933936{col 37}{space 1}    6.45{col 46}{space 3}0.000{col 54}{space 4} .4195436{col 67}{space 3} .7856399
{txt}{space 7}1997  {c |}{col 14}{res}{space 2} .7698976{col 26}{space 2} .0914806{col 37}{space 1}    8.42{col 46}{space 3}0.000{col 54}{space 4}  .590599{col 67}{space 3} .9491962
{txt}{space 7}1998  {c |}{col 14}{res}{space 2} 1.353066{col 26}{space 2} .0844785{col 37}{space 1}   16.02{col 46}{space 3}0.000{col 54}{space 4} 1.187491{col 67}{space 3}  1.51864
{txt}{space 7}1999  {c |}{col 14}{res}{space 2} 1.170266{col 26}{space 2} .0855308{col 37}{space 1}   13.68{col 46}{space 3}0.000{col 54}{space 4} 1.002629{col 67}{space 3} 1.337903
{txt}{space 7}2000  {c |}{col 14}{res}{space 2} 1.203335{col 26}{space 2} .0851824{col 37}{space 1}   14.13{col 46}{space 3}0.000{col 54}{space 4}  1.03638{col 67}{space 3} 1.370289
{txt}{space 7}2001  {c |}{col 14}{res}{space 2} .7817104{col 26}{space 2} .0897631{col 37}{space 1}    8.71{col 46}{space 3}0.000{col 54}{space 4}  .605778{col 67}{space 3} .9576428
{txt}{space 7}2002  {c |}{col 14}{res}{space 2} 1.038417{col 26}{space 2} .0871789{col 37}{space 1}   11.91{col 46}{space 3}0.000{col 54}{space 4} .8675499{col 67}{space 3} 1.209285
{txt}{space 7}2003  {c |}{col 14}{res}{space 2} .9295247{col 26}{space 2} .0882839{col 37}{space 1}   10.53{col 46}{space 3}0.000{col 54}{space 4} .7564914{col 67}{space 3} 1.102558
{txt}{space 7}2004  {c |}{col 14}{res}{space 2} .8013483{col 26}{space 2} .0909023{col 37}{space 1}    8.82{col 46}{space 3}0.000{col 54}{space 4}  .623183{col 67}{space 3} .9795136
{txt}{space 7}2005  {c |}{col 14}{res}{space 2} .4824933{col 26}{space 2} .0987618{col 37}{space 1}    4.89{col 46}{space 3}0.000{col 54}{space 4} .2889237{col 67}{space 3} .6760629
{txt}{space 7}2006  {c |}{col 14}{res}{space 2} .7244172{col 26}{space 2} .0966159{col 37}{space 1}    7.50{col 46}{space 3}0.000{col 54}{space 4} .5350536{col 67}{space 3} .9137808
{txt}{space 7}2007  {c |}{col 14}{res}{space 2} .7410066{col 26}{space 2} .0974166{col 37}{space 1}    7.61{col 46}{space 3}0.000{col 54}{space 4} .5500735{col 67}{space 3} .9319397
{txt}{space 7}2008  {c |}{col 14}{res}{space 2} .9578738{col 26}{space 2} .0935052{col 37}{space 1}   10.24{col 46}{space 3}0.000{col 54}{space 4}  .774607{col 67}{space 3} 1.141141
{txt}{space 7}2009  {c |}{col 14}{res}{space 2} .9815403{col 26}{space 2} .0932564{col 37}{space 1}   10.53{col 46}{space 3}0.000{col 54}{space 4} .7987611{col 67}{space 3} 1.164319
{txt}{space 7}2010  {c |}{col 14}{res}{space 2} .7027552{col 26}{space 2} .0989909{col 37}{space 1}    7.10{col 46}{space 3}0.000{col 54}{space 4} .5087367{col 67}{space 3} .8967738
{txt}{space 7}2011  {c |}{col 14}{res}{space 2} 1.417786{col 26}{space 2} .0888848{col 37}{space 1}   15.95{col 46}{space 3}0.000{col 54}{space 4} 1.243575{col 67}{space 3} 1.591997
{txt}{space 7}2012  {c |}{col 14}{res}{space 2} 1.452336{col 26}{space 2} .0875695{col 37}{space 1}   16.58{col 46}{space 3}0.000{col 54}{space 4} 1.280703{col 67}{space 3}  1.62397
{txt}{space 7}2013  {c |}{col 14}{res}{space 2}  1.38737{col 26}{space 2} .0880238{col 37}{space 1}   15.76{col 46}{space 3}0.000{col 54}{space 4} 1.214846{col 67}{space 3} 1.559893
{txt}{space 7}2014  {c |}{col 14}{res}{space 2} 1.639447{col 26}{space 2} .0859215{col 37}{space 1}   19.08{col 46}{space 3}0.000{col 54}{space 4} 1.471044{col 67}{space 3}  1.80785
{txt}{space 7}2015  {c |}{col 14}{res}{space 2} 1.591718{col 26}{space 2} .0859576{col 37}{space 1}   18.52{col 46}{space 3}0.000{col 54}{space 4} 1.423244{col 67}{space 3} 1.760192
{txt}{space 7}2016  {c |}{col 14}{res}{space 2} 1.568586{col 26}{space 2} .0850559{col 37}{space 1}   18.44{col 46}{space 3}0.000{col 54}{space 4}  1.40188{col 67}{space 3} 1.735292
{txt}{space 7}2017  {c |}{col 14}{res}{space 2} 1.623728{col 26}{space 2} .0844351{col 37}{space 1}   19.23{col 46}{space 3}0.000{col 54}{space 4} 1.458239{col 67}{space 3} 1.789218
{txt}{space 12} {c |}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0827484{col 26}{space 2} .0511244{col 37}{space 1}    1.62{col 46}{space 3}0.106{col 54}{space 4}-.0174536{col 67}{space 3} .1829504
{txt}{space 8}temp {c |}{col 14}{res}{space 2} .0011584{col 26}{space 2}  .003155{col 37}{space 1}    0.37{col 46}{space 3}0.713{col 54}{space 4}-.0050252{col 67}{space 3}  .007342
{txt}{space 8}prec {c |}{col 14}{res}{space 2}-.0003202{col 26}{space 2} .0001779{col 37}{space 1}   -1.80{col 46}{space 3}0.072{col 54}{space 4}-.0006689{col 67}{space 3} .0000285
{txt}{space 2}py_UCDP_bi {c |}{col 14}{res}{space 2}-.3806054{col 26}{space 2} .0075528{col 37}{space 1}  -50.39{col 46}{space 3}0.000{col 54}{space 4}-.3954086{col 67}{space 3}-.3658022
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est6{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. 
. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Appendix_TblA1_Logit.csv", label nogaps compress 
> keep(idle_index)  se star(* 0.05 ** 0.01 *** 0.001) 
> stats(perch N r2 FEobj FEoy FEcountry FEmo TP PY, fmt(%3.2f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Country-Year FE"' `"Country FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Appendix_TblA1_Logit.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. 
. ***************************************************************************************
. ***************************************************************************************
. ****** Table A2: . Estimations results for count dependent variables
. ***************************************************************************************
. ***************************************************************************************
. 
. gen SCAD_count=0
{txt}
{com}. replace SCAD_count = n_etype8+n_etype9 if n_etype8>0 & n_etype9>0
{txt}(363 real changes made)

{com}. replace SCAD_count = n_etype8 if n_etype8>0 & n_etype9==.
{txt}(0 real changes made)

{com}. replace SCAD_count = n_etype9 if n_etype8==. & n_etype9>0
{txt}(0 real changes made)

{com}. replace SCAD_count = . if n_etype8==. & n_etype9==.
{txt}(0 real changes made)

{com}. 
. 
. sum SCAD_count UCDP_Violent_init_count ACLED_initiator_count

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}SCAD_count {c |}{res}    277,872     .005337    .1935276          0         30
{txt}UCD~it_count {c |}{res}    277,872     .090207    .7884898          0         73
{txt}ACLED_init~t {c |}{res}    208,404    .2787758    1.977493          0        100
{txt}
{com}. 
. 
. kdensity SCAD_count
{res}{txt}
{com}. 
. kdensity UCDP_Violent_init_count 
{res}{txt}
{com}. 
. kdensity ACLED_initiator_count
{res}{txt}
{com}. 
. 
. ** large difference between s.d. and mean means, the data does not follow poisson distribution, so we use Negative Binomial 
. 
. set matsize 10000
{txt}
{com}. 
. xtset objectid ym
{res}{txt}{col 8}panel variable:  {res}objectid (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}ym, 360 to 695
{txt}{col 17}delta:  {res}1 unit
{txt}
{com}. 
. est clear
{txt}
{com}. 
. eststo: reghdfe SCAD_count idle_index temp prec py_SCADantigov, absorb(oyfe) vce(r) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   241,248
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res} 221140{txt}){col 67}= {res}      0.77
{txt}{col 51}Prob > F{col 67}= {res}    0.5450
{txt}{col 51}R-squared{col 67}= {res}    0.4566
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4071
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0000
{txt}{col 51}Root MSE{col 67}= {res}    0.1599

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}    SCAD_count{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}idle_index {c |}{col 16}{res}{space 2} .0024089{col 28}{space 2} .0018763{col 39}{space 1}    1.28{col 48}{space 3}0.199{col 56}{space 4}-.0012687{col 69}{space 3} .0060865
{txt}{space 10}temp {c |}{col 16}{res}{space 2} .0000675{col 28}{space 2} .0001105{col 39}{space 1}    0.61{col 48}{space 3}0.541{col 56}{space 4}-.0001491{col 69}{space 3} .0002842
{txt}{space 10}prec {c |}{col 16}{res}{space 2} 1.89e-06{col 28}{space 2} 3.30e-06{col 39}{space 1}    0.57{col 48}{space 3}0.566{col 56}{space 4}-4.57e-06{col 69}{space 3} 8.36e-06
{txt}py_SCADantigov {c |}{col 16}{res}{space 2} .0005021{col 28}{space 2} .0004569{col 39}{space 1}    1.10{col 48}{space 3}0.272{col 56}{space 4}-.0003933{col 69}{space 3} .0013976
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}-.0015859{col 28}{space 2} .0051891{col 39}{space 1}   -0.31{col 48}{space 3}0.760{col 56}{space 4}-.0117564{col 69}{space 3} .0085847
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20104{col 27}{space 1}        0{col 39}{result}{space 1}    20104{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}.  
. eststo: reghdfe ACLED_initiator_count idle_index temp prec py_acled_bi , absorb(oyfe) vce(r)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   180,936
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res} 165854{txt}){col 67}= {res}     57.99
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.6958
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6681
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0008
{txt}{col 51}Root MSE{col 67}= {res}    1.2178

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}ACLED_init~t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0242707{col 26}{space 2} .0110402{col 37}{space 1}    2.20{col 46}{space 3}0.028{col 54}{space 4} .0026321{col 67}{space 3} .0459094
{txt}{space 8}temp {c |}{col 14}{res}{space 2}  .001379{col 26}{space 2} .0006375{col 37}{space 1}    2.16{col 46}{space 3}0.031{col 54}{space 4} .0001294{col 67}{space 3} .0026286
{txt}{space 8}prec {c |}{col 14}{res}{space 2}-.0001162{col 26}{space 2}  .000035{col 37}{space 1}   -3.32{col 46}{space 3}0.001{col 54}{space 4}-.0001847{col 67}{space 3}-.0000477
{txt}{space 1}py_acled_bi {c |}{col 14}{res}{space 2} .0346464{col 26}{space 2} .0024287{col 37}{space 1}   14.27{col 46}{space 3}0.000{col 54}{space 4} .0298862{col 67}{space 3} .0394066
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1305061{col 26}{space 2} .0197295{col 37}{space 1}    6.61{col 46}{space 3}0.000{col 54}{space 4} .0918367{col 67}{space 3} .1691755
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15078{col 27}{space 1}        0{col 39}{result}{space 1}    15078{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est2{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}.   
. eststo: reghdfe UCDP_Violent_init_count idle_index temp prec py_UCDP_bi , absorb(oyfe) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   241,248
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res} 221140{txt}){col 67}= {res}     24.17
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.6185
{txt}{col 51}Adj R-squared{col 67}= {res}    0.5839
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0016
{txt}{col 51}Root MSE{col 67}= {res}    0.5447

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}UCD~it_count{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0092756{col 26}{space 2} .0046115{col 37}{space 1}    2.01{col 46}{space 3}0.044{col 54}{space 4} .0002373{col 67}{space 3}  .018314
{txt}{space 8}temp {c |}{col 14}{res}{space 2} .0003867{col 26}{space 2} .0002768{col 37}{space 1}    1.40{col 46}{space 3}0.162{col 54}{space 4}-.0001558{col 67}{space 3} .0009292
{txt}{space 8}prec {c |}{col 14}{res}{space 2} -.000031{col 26}{space 2} .0000129{col 37}{space 1}   -2.41{col 46}{space 3}0.016{col 54}{space 4}-.0000563{col 67}{space 3}-5.79e-06
{txt}{space 2}py_UCDP_bi {c |}{col 14}{res}{space 2}  .027453{col 26}{space 2} .0031636{col 37}{space 1}    8.68{col 46}{space 3}0.000{col 54}{space 4} .0212525{col 67}{space 3} .0336536
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.1443104{col 26}{space 2} .0276348{col 37}{space 1}   -5.22{col 46}{space 3}0.000{col 54}{space 4}-.1984739{col 67}{space 3}-.0901469
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20104{col 27}{space 1}        0{col 39}{result}{space 1}    20104{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. 
. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Appendix_TblA2_Count.csv", label nogaps compress 
> keep(idle_index)  se star(* 0.05 ** 0.01 *** 0.001) 
> stats(perch N r2 FEobj FEoy FEcountry FEmo TP PY, fmt(%3.2f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Country-Year FE"' `"Country FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Appendix_TblA2_Count.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. 
. 
. 
. 
. 
. ***************************************************************************************
. ***************************************************************************************
. ****** Table A3: SCAD outcomes excluding desserts (areas without crops).
. ***************************************************************************************
. ***************************************************************************************
. 
. 
. sort oyfe 
{txt}
{com}. by oyfe: egen idleyear = min(idle_index)
{txt}(34944 missing values generated)

{com}. 
. est clear 
{txt}
{com}. sum SCADantigov if sample==1 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}SCADantigov {c |}{res}    242,928    .0152185    .1224212          0          1
{txt}
{com}. local bl = r(mean) 
{txt}
{com}. 
. eststo: reghdfe SCADantigov idle_index if idleyear!=1, absorb(objectid ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   226,128
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 225454{txt}){col 67}= {res}     11.82
{txt}{col 51}Prob > F{col 67}= {res}    0.0006
{txt}{col 51}R-squared{col 67}= {res}    0.0779
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0752
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1184

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0031646{col 26}{space 2} .0009203{col 37}{space 1}    3.44{col 46}{space 3}0.001{col 54}{space 4} .0013608{col 67}{space 3} .0049684
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0139909{col 26}{space 2} .0004668{col 37}{space 1}   29.97{col 46}{space 3}0.000{col 54}{space 4}  .013076{col 67}{space 3} .0149058
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      673{col 27}{space 1}        0{col 39}{result}{space 1}      673{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:20.7942349289938}"

{com}. di  ((_b[idle_index]*.35)/`bl')*100
{res}7.2779822
{txt}
{com}. //estadd local perch50 =  ((_b[idle_index]*.63)/`bl')*100
. 
. eststo: reghdfe SCADantigov idle_index if idleyear!=1, absorb(oyfe ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   226,128
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res} 207283{txt}){col 67}= {res}     15.28
{txt}{col 51}Prob > F{col 67}= {res}    0.0001
{txt}{col 51}R-squared{col 67}= {res}    0.3218
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2601
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1059

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0031646{col 26}{space 2} .0008097{col 37}{space 1}    3.91{col 46}{space 3}0.000{col 54}{space 4} .0015776{col 67}{space 3} .0047515
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0139909{col 26}{space 2} .0004086{col 37}{space 1}   34.24{col 46}{space 3}0.000{col 54}{space 4} .0131899{col 67}{space 3} .0147918
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    18844{col 27}{space 1}        0{col 39}{result}{space 1}    18844{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est2{txt} stored)

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:20.79423492899339}"

{com}. 
. eststo: reghdfe SCADantigov idle_index if idleyear!=1, absorb(objectid oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   226,128
{txt}Absorbing 2 HDFE groups{col 51}F({res}   1{txt},{res} 207283{txt}){col 67}= {res}     15.28
{txt}{col 51}Prob > F{col 67}= {res}    0.0001
{txt}{col 51}R-squared{col 67}= {res}    0.3218
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2601
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1059

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0031646{col 26}{space 2} .0008097{col 37}{space 1}    3.91{col 46}{space 3}0.000{col 54}{space 4} .0015776{col 67}{space 3} .0047515
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0139909{col 26}{space 2} .0004086{col 37}{space 1}   34.24{col 46}{space 3}0.000{col 54}{space 4} .0131899{col 67}{space 3} .0147918
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      673{col 27}{space 1}        0{col 39}{result}{space 1}      673{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    18844{col 27}{space 1}      673{col 39}{result}{space 1}    18171{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:20.79423492899337}"

{com}. 
. eststo: reghdfe SCADantigov idle_index if idleyear!=1, absorb(objectid oyfe ym ) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   226,128
{txt}Absorbing 3 HDFE groups{col 51}F({res}   1{txt},{res} 206975{txt}){col 67}= {res}     17.86
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3230
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2604
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1059

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0034851{col 26}{space 2} .0008248{col 37}{space 1}    4.23{col 46}{space 3}0.000{col 54}{space 4} .0018686{col 67}{space 3} .0051016
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0138483{col 26}{space 2} .0004147{col 37}{space 1}   33.39{col 46}{space 3}0.000{col 54}{space 4} .0130355{col 67}{space 3} .0146611
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      673{col 27}{space 1}        0{col 39}{result}{space 1}      673{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    18844{col 27}{space 1}      673{col 39}{result}{space 1}    18171{col 53}{text} {col 54}{c |}
{col 1}{text}          ym{col 14}{c |}{space 1}      336{col 27}{space 1}       28{col 39}{result}{space 1}      308{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est4{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:22.9006247312535}"

{com}. 
. eststo: reghdfe SCADantigov idle_index temp prec if idleyear!=1, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   225,120
{txt}Absorbing 3 HDFE groups{col 51}F({res}   3{txt},{res} 206346{txt}){col 67}= {res}      6.92
{txt}{col 51}Prob > F{col 67}= {res}    0.0001
{txt}{col 51}R-squared{col 67}= {res}    0.3223
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2607
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0001
{txt}{col 51}Root MSE{col 67}= {res}    0.1060

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} SCADantigov{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}idle_index {c |}{col 14}{res}{space 2} .0027983{col 26}{space 2} .0009241{col 37}{space 1}    3.03{col 46}{space 3}0.002{col 54}{space 4} .0009871{col 67}{space 3} .0046094
{txt}{space 8}temp {c |}{col 14}{res}{space 2} .0000867{col 26}{space 2} .0000671{col 37}{space 1}    1.29{col 46}{space 3}0.196{col 54}{space 4}-.0000447{col 67}{space 3} .0002181
{txt}{space 8}prec {c |}{col 14}{res}{space 2}-4.02e-06{col 26}{space 2} 2.84e-06{col 37}{space 1}   -1.41{col 46}{space 3}0.157{col 54}{space 4}-9.58e-06{col 67}{space 3} 1.55e-06
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0124735{col 26}{space 2} .0016064{col 37}{space 1}    7.76{col 46}{space 3}0.000{col 54}{space 4} .0093249{col 67}{space 3} .0156221
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      670{col 27}{space 1}        0{col 39}{result}{space 1}      670{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    18760{col 27}{space 1}      670{col 39}{result}{space 1}    18090{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est5{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:18.3873036570253}"

{com}. 
. eststo: reghdfe SCADantigov idle_index py_SCADantigov if idleyear!=1, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   226,128
{txt}Absorbing 3 HDFE groups{col 51}F({res}   2{txt},{res} 207271{txt}){col 67}= {res}    147.91
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3345
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2740
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0187
{txt}{col 51}Root MSE{col 67}= {res}    0.1049

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}   SCADantigov{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}idle_index {c |}{col 16}{res}{space 2} .0028464{col 28}{space 2} .0008132{col 39}{space 1}    3.50{col 48}{space 3}0.000{col 56}{space 4} .0012525{col 69}{space 3} .0044402
{txt}py_SCADantigov {c |}{col 16}{res}{space 2} .0133512{col 28}{space 2} .0007907{col 39}{space 1}   16.89{col 48}{space 3}0.000{col 56}{space 4} .0118014{col 69}{space 3} .0149009
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}-.1133828{col 28}{space 2} .0075121{col 39}{space 1}  -15.09{col 48}{space 3}0.000{col 56}{space 4}-.1281064{col 69}{space 3}-.0986592
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      673{col 27}{space 1}        0{col 39}{result}{space 1}      673{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    18844{col 27}{space 1}      673{col 39}{result}{space 1}    18171{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est6{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:18.70336536215708}"

{com}. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Appendix_TblA3_desert.csv", label nogaps compress 
> keep(idle_index)  se star(* 0.05 ** 0.01 *** 0.001) cells(b(star fmt(%9.4f)) se( fmt(%9.4f)))
> stats(perch N r2 FEobj FEoy FEcountry FEmo TP PY, fmt(%2.1f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Country-Year FE"' `"Country FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Appendix_TblA3_desert.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. 
. ***************************************************************************************
. ***************************************************************************************
. ****** Table A4: See Above (Figure 3)
. ***************************************************************************************
. ***************************************************************************************
. 
. 
. 
. ***************************************************************************************
. ***************************************************************************************
. ****** Table A5: Models with spatially weighted lagged dependent variables
. ***************************************************************************************
. ***************************************************************************************
. 
. **SCAD
. 
. est clear 
{txt}
{com}. sum SCADantigov if sample==1 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}SCADantigov {c |}{res}    242,928    .0152185    .1224212          0          1
{txt}
{com}. local bl = r(mean) 
{txt}
{com}. 
. eststo: reghdfe SCADantigov wy_SCADantigov_1 idle_index , absorb(objectid ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res} 242203{txt}){col 67}= {res}    805.99
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1022
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0995
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0262
{txt}{col 51}Root MSE{col 67}= {res}    0.1162

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     SCADantigov{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_SCADantigov_1 {c |}{col 18}{res}{space 2} 1.242001{col 30}{space 2} .0310032{col 41}{space 1}   40.06{col 50}{space 3}0.000{col 58}{space 4} 1.181236{col 71}{space 3} 1.302767
{txt}{space 6}idle_index {c |}{col 18}{res}{space 2} .0024515{col 30}{space 2} .0009069{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .0006739{col 71}{space 3}  .004229
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0007328{col 30}{space 2} .0005293{col 41}{space 1}   -1.38{col 50}{space 3}0.166{col 58}{space 4}-.0017701{col 71}{space 3} .0003045
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:16.10848774319715}"

{com}. di  ((_b[idle_index]*.35)/`bl')*100
{res}5.6379707
{txt}
{com}. //estadd local perch50 =  ((_b[idle_index]*.63)/`bl')*100
. 
. eststo: reghdfe SCADantigov wy_SCADantigov_1 idle_index , absorb(oyfe ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res} 222682{txt}){col 67}= {res}     18.88
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3270
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2658
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0004
{txt}{col 51}Root MSE{col 67}= {res}    0.1049

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     SCADantigov{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_SCADantigov_1 {c |}{col 18}{res}{space 2} .2916084{col 30}{space 2} .0614748{col 41}{space 1}    4.74{col 50}{space 3}0.000{col 58}{space 4} .1711195{col 71}{space 3} .4120974
{txt}{space 6}idle_index {c |}{col 18}{res}{space 2} .0029971{col 30}{space 2} .0008105{col 41}{space 1}    3.70{col 50}{space 3}0.000{col 58}{space 4} .0014086{col 71}{space 3} .0045857
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0103033{col 30}{space 2} .0008255{col 41}{space 1}   12.48{col 50}{space 3}0.000{col 58}{space 4} .0086853{col 71}{space 3} .0119213
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}        0{col 39}{result}{space 1}    20244{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est2{txt} stored)

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:19.69407220219946}"

{com}. 
. eststo: reghdfe SCADantigov wy_SCADantigov_1 idle_index , absorb(objectid oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 2 HDFE groups{col 51}F({res}   2{txt},{res} 222682{txt}){col 67}= {res}     18.88
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3270
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2658
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0004
{txt}{col 51}Root MSE{col 67}= {res}    0.1049

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     SCADantigov{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_SCADantigov_1 {c |}{col 18}{res}{space 2} .2916084{col 30}{space 2} .0614748{col 41}{space 1}    4.74{col 50}{space 3}0.000{col 58}{space 4} .1711195{col 71}{space 3} .4120974
{txt}{space 6}idle_index {c |}{col 18}{res}{space 2} .0029971{col 30}{space 2} .0008105{col 41}{space 1}    3.70{col 50}{space 3}0.000{col 58}{space 4} .0014086{col 71}{space 3} .0045857
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0103033{col 30}{space 2} .0008255{col 41}{space 1}   12.48{col 50}{space 3}0.000{col 58}{space 4} .0086853{col 71}{space 3} .0119213
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:19.69407220219933}"

{com}. 
. eststo: reghdfe SCADantigov wy_SCADantigov_1 idle_index , absorb(objectid oyfe ym ) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 3 HDFE groups{col 51}F({res}   2{txt},{res} 222374{txt}){col 67}= {res}     19.70
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3282
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2661
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0004
{txt}{col 51}Root MSE{col 67}= {res}    0.1049

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     SCADantigov{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_SCADantigov_1 {c |}{col 18}{res}{space 2} .3508388{col 30}{space 2} .0754448{col 41}{space 1}    4.65{col 50}{space 3}0.000{col 58}{space 4} .2029689{col 71}{space 3} .4987087
{txt}{space 6}idle_index {c |}{col 18}{res}{space 2} .0033262{col 30}{space 2} .0008238{col 41}{space 1}    4.04{col 50}{space 3}0.000{col 58}{space 4} .0017115{col 71}{space 3} .0049408
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0094401{col 30}{space 2} .0009755{col 41}{space 1}    9.68{col 50}{space 3}0.000{col 58}{space 4} .0075281{col 71}{space 3} .0113521
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}          ym{col 14}{c |}{space 1}      336{col 27}{space 1}       28{col 39}{result}{space 1}      308{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est4{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:21.85619105006239}"

{com}. 
. eststo: reghdfe SCADantigov wy_SCADantigov_1 idle_index temp prec, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   241,248
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res} 221129{txt}){col 67}= {res}     10.88
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3276
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2664
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0005
{txt}{col 51}Root MSE{col 67}= {res}    0.1051

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     SCADantigov{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_SCADantigov_1 {c |}{col 18}{res}{space 2} .3074293{col 30}{space 2} .0627364{col 41}{space 1}    4.90{col 50}{space 3}0.000{col 58}{space 4} .1844675{col 71}{space 3}  .430391
{txt}{space 6}idle_index {c |}{col 18}{res}{space 2} .0027678{col 30}{space 2} .0009154{col 41}{space 1}    3.02{col 50}{space 3}0.002{col 58}{space 4} .0009736{col 71}{space 3} .0045619
{txt}{space 12}temp {c |}{col 18}{res}{space 2} .0000385{col 30}{space 2} .0000595{col 41}{space 1}    0.65{col 50}{space 3}0.517{col 58}{space 4}-.0000781{col 71}{space 3} .0001552
{txt}{space 12}prec {c |}{col 18}{res}{space 2}-3.47e-06{col 30}{space 2} 2.77e-06{col 41}{space 1}   -1.25{col 50}{space 3}0.210{col 58}{space 4}-8.91e-06{col 71}{space 3} 1.96e-06
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0096489{col 30}{space 2} .0016115{col 41}{space 1}    5.99{col 50}{space 3}0.000{col 58}{space 4} .0064903{col 71}{space 3} .0128074
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      718{col 27}{space 1}        0{col 39}{result}{space 1}      718{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20104{col 27}{space 1}      718{col 39}{result}{space 1}    19386{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est5{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:18.18702390954614}"

{com}. 
. eststo: reghdfe SCADantigov wy_SCADantigov_1 idle_index py_SCADantigov, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 3 HDFE groups{col 51}F({res}   3{txt},{res} 222670{txt}){col 67}= {res}    113.11
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3397
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2796
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0191
{txt}{col 51}Root MSE{col 67}= {res}    0.1039

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     SCADantigov{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_SCADantigov_1 {c |}{col 18}{res}{space 2} .3269142{col 30}{space 2} .0625954{col 41}{space 1}    5.22{col 50}{space 3}0.000{col 58}{space 4} .2042288{col 71}{space 3} .4495995
{txt}{space 6}idle_index {c |}{col 18}{res}{space 2} .0027201{col 30}{space 2} .0008122{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .0011281{col 71}{space 3} .0043121
{txt}{space 2}py_SCADantigov {c |}{col 18}{res}{space 2} .0130642{col 30}{space 2} .0007493{col 41}{space 1}   17.44{col 50}{space 3}0.000{col 58}{space 4} .0115956{col 71}{space 3} .0145328
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.1154874{col 30}{space 2} .0072099{col 41}{space 1}  -16.02{col 50}{space 3}0.000{col 58}{space 4}-.1296186{col 71}{space 3}-.1013561
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est6{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:17.87358906468484}"

{com}. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Appendix_TblA5_WYDV_SCAD.csv", label nogaps compress 
> keep(idle_index wy_SCADantigov_1)  se star(* 0.05 ** 0.01 *** 0.001) cells(b(star fmt(%9.4f)) se( fmt(%9.4f)))
> stats(perch N r2 FEobj FEoy FEcountry FEmo TP PY, fmt(%2.1f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Country-Year FE"' `"Country FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Appendix_TblA5_WYDV_SCAD.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. *********************************************************
. 
. *ACLED
. 
. sum acled_bi if sample==1 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}acled_bi {c |}{res}    182,196    .0837505     .277014          0          1
{txt}
{com}. local bl = r(mean) 
{txt}
{com}. 
. est clear
{txt}
{com}. eststo: reghdfe acled_bi wy_acled_bi_1 idle_index , absorb(objectid ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   182,196
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res} 181471{txt}){col 67}= {res}   2816.98
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.2638
{txt}{col 51}Adj R-squared{col 67}= {res}    0.2609
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0581
{txt}{col 51}Root MSE{col 67}= {res}    0.2382

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}     acled_bi{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      t{col 47}   P>|t|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_acled_bi_1 {c |}{col 15}{res}{space 2}  1.64812{col 27}{space 2} .0219841{col 38}{space 1}   74.97{col 47}{space 3}0.000{col 55}{space 4} 1.605032{col 68}{space 3} 1.691208
{txt}{space 3}idle_index {c |}{col 15}{res}{space 2} .0065917{col 27}{space 2} .0020498{col 38}{space 1}    3.22{col 47}{space 3}0.001{col 55}{space 4} .0025741{col 68}{space 3} .0106093
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} -.043416{col 27}{space 2} .0018467{col 38}{space 1}  -23.51{col 47}{space 3}0.000{col 55}{space 4}-.0470354{col 68}{space 3}-.0397966
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:7.870611374656431}"

{com}. 
. eststo: reghdfe acled_bi wy_acled_bi_1 idle_index , absorb( oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   182,196
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res} 167011{txt}){col 67}= {res}     86.85
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4696
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4214
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0019
{txt}{col 51}Root MSE{col 67}= {res}    0.2107

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}     acled_bi{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      t{col 47}   P>|t|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_acled_bi_1 {c |}{col 15}{res}{space 2} .5000629{col 27}{space 2} .0403254{col 38}{space 1}   12.40{col 47}{space 3}0.000{col 55}{space 4} .4210259{col 68}{space 3} .5790998
{txt}{space 3}idle_index {c |}{col 15}{res}{space 2} .0077771{col 27}{space 2} .0018036{col 38}{space 1}    4.31{col 47}{space 3}0.000{col 55}{space 4}  .004242{col 68}{space 3} .0113122
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .0423751{col 27}{space 2} .0031647{col 38}{space 1}   13.39{col 47}{space 3}0.000{col 55}{space 4} .0361724{col 68}{space 3} .0485779
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15183{col 27}{space 1}        0{col 39}{result}{space 1}    15183{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est2{txt} stored)

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:9.285986113441338}"

{com}. 
. eststo: reghdfe acled_bi wy_acled_bi_1 idle_index , absorb(objectid oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   182,196
{txt}Absorbing 2 HDFE groups{col 51}F({res}   2{txt},{res} 167011{txt}){col 67}= {res}     86.85
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4696
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4214
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0019
{txt}{col 51}Root MSE{col 67}= {res}    0.2107

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}     acled_bi{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      t{col 47}   P>|t|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_acled_bi_1 {c |}{col 15}{res}{space 2} .5000629{col 27}{space 2} .0403254{col 38}{space 1}   12.40{col 47}{space 3}0.000{col 55}{space 4} .4210259{col 68}{space 3} .5790998
{txt}{space 3}idle_index {c |}{col 15}{res}{space 2} .0077771{col 27}{space 2} .0018036{col 38}{space 1}    4.31{col 47}{space 3}0.000{col 55}{space 4}  .004242{col 68}{space 3} .0113122
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .0423751{col 27}{space 2} .0031647{col 38}{space 1}   13.39{col 47}{space 3}0.000{col 55}{space 4} .0361724{col 68}{space 3} .0485779
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15183{col 27}{space 1}      723{col 39}{result}{space 1}    14460{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:9.285986113441357}"

{com}. 
. eststo: reghdfe acled_bi wy_acled_bi_1 idle_index , absorb(objectid oyfe mon ) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   182,196
{txt}Absorbing 3 HDFE groups{col 51}F({res}   2{txt},{res} 167000{txt}){col 67}= {res}     88.84
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4697
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4215
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0019
{txt}{col 51}Root MSE{col 67}= {res}    0.2107

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}     acled_bi{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      t{col 47}   P>|t|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_acled_bi_1 {c |}{col 15}{res}{space 2} .5058603{col 27}{space 2} .0411899{col 38}{space 1}   12.28{col 47}{space 3}0.000{col 55}{space 4}  .425129{col 68}{space 3} .5865917
{txt}{space 3}idle_index {c |}{col 15}{res}{space 2} .0092432{col 27}{space 2} .0018433{col 38}{space 1}    5.01{col 47}{space 3}0.000{col 55}{space 4} .0056303{col 68}{space 3} .0128561
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .0412306{col 27}{space 2} .0032292{col 38}{space 1}   12.77{col 47}{space 3}0.000{col 55}{space 4} .0349015{col 68}{space 3} .0475598
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15183{col 27}{space 1}      723{col 39}{result}{space 1}    14460{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est4{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:11.03662007582554}"

{com}. 
. eststo: reghdfe acled_bi wy_acled_bi_1 idle_index temp prec, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   180,936
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res} 165843{txt}){col 67}= {res}     47.63
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4708
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4227
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0020
{txt}{col 51}Root MSE{col 67}= {res}    0.2108

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}     acled_bi{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      t{col 47}   P>|t|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_acled_bi_1 {c |}{col 15}{res}{space 2} .5052361{col 27}{space 2} .0413687{col 38}{space 1}   12.21{col 47}{space 3}0.000{col 55}{space 4} .4241544{col 68}{space 3} .5863178
{txt}{space 3}idle_index {c |}{col 15}{res}{space 2} .0074543{col 27}{space 2} .0020482{col 38}{space 1}    3.64{col 47}{space 3}0.000{col 55}{space 4} .0034399{col 68}{space 3} .0114688
{txt}{space 9}temp {c |}{col 15}{res}{space 2} .0004112{col 27}{space 2} .0001387{col 38}{space 1}    2.96{col 47}{space 3}0.003{col 55}{space 4} .0001393{col 68}{space 3}  .000683
{txt}{space 9}prec {c |}{col 15}{res}{space 2}-.0000126{col 27}{space 2} 6.58e-06{col 38}{space 1}   -1.92{col 47}{space 3}0.054{col 55}{space 4}-.0000255{col 68}{space 3} 2.41e-07
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .0336773{col 27}{space 2} .0045096{col 38}{space 1}    7.47{col 47}{space 3}0.000{col 55}{space 4} .0248386{col 68}{space 3} .0425159
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      718{col 27}{space 1}        0{col 39}{result}{space 1}      718{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15078{col 27}{space 1}      718{col 39}{result}{space 1}    14360{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est5{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:8.900656042662874}"

{com}. 
. eststo: reghdfe acled_bi wy_acled_bi_1 idle_index py_acled_bi, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   182,196
{txt}Absorbing 3 HDFE groups{col 51}F({res}   3{txt},{res} 166999{txt}){col 67}= {res}    233.83
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4758
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4282
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0134
{txt}{col 51}Root MSE{col 67}= {res}    0.2095

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}     acled_bi{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      t{col 47}   P>|t|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_acled_bi_1 {c |}{col 15}{res}{space 2} .5072311{col 27}{space 2} .0410483{col 38}{space 1}   12.36{col 47}{space 3}0.000{col 55}{space 4} .4267773{col 68}{space 3} .5876849
{txt}{space 3}idle_index {c |}{col 15}{res}{space 2} .0092158{col 27}{space 2} .0018294{col 38}{space 1}    5.04{col 47}{space 3}0.000{col 55}{space 4} .0056302{col 68}{space 3} .0128015
{txt}{space 2}py_acled_bi {c |}{col 15}{res}{space 2} .0260278{col 27}{space 2} .0011312{col 38}{space 1}   23.01{col 47}{space 3}0.000{col 55}{space 4} .0238107{col 68}{space 3} .0282449
{txt}{space 8}_cons {c |}{col 15}{res}{space 2}-.0720235{col 27}{space 2} .0058331{col 38}{space 1}  -12.35{col 47}{space 3}0.000{col 55}{space 4}-.0834562{col 68}{space 3}-.0605908
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    15183{col 27}{space 1}      723{col 39}{result}{space 1}    14460{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est6{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:11.00391788319642}"

{com}. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Appendix_TblA5_WYDV_ACLED.csv", label nogaps compress 
> keep(idle_index wy_acled_bi_1)  se star(* 0.05 ** 0.01 *** 0.001) 
> stats(perch N r2 FEobj FEoy FEmo TP PY, fmt(%3.2f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Location-Year FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Appendix_TblA5_WYDV_ACLED.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. ***************************************
. 
. *UCDP
. 
. est clear 
{txt}
{com}. sum UCDP_bi if sample_ucdp==1 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}UCDP_bi {c |}{res}    242,928    .0421195    .2008621          0          1
{txt}
{com}. local bl = r(mean) 
{txt}
{com}. 
. 
. est clear
{txt}
{com}. eststo: reghdfe UCDP_bi wy_UCDP_bi_1 idle_index , absorb(objectid ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res} 242203{txt}){col 67}= {res}    793.19
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1887
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1863
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0177
{txt}{col 51}Root MSE{col 67}= {res}    0.1812

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_UCDP_bi_1 {c |}{col 14}{res}{space 2} .9800165{col 26}{space 2} .0246414{col 37}{space 1}   39.77{col 46}{space 3}0.000{col 54}{space 4}   .93172{col 67}{space 3} 1.028313
{txt}{space 2}idle_index {c |}{col 14}{res}{space 2} .0033122{col 26}{space 2} .0013392{col 37}{space 1}    2.47{col 46}{space 3}0.013{col 54}{space 4} .0006875{col 67}{space 3} .0059369
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0118095{col 26}{space 2} .0009766{col 37}{space 1}   12.09{col 46}{space 3}0.000{col 54}{space 4} .0098955{col 67}{space 3} .0137236
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est1{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:7.863772437401323}"

{com}. 
. eststo: reghdfe UCDP_bi wy_UCDP_bi_1 idle_index , absorb( oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res} 222682{txt}){col 67}= {res}     26.66
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4539
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4043
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0006
{txt}{col 51}Root MSE{col 67}= {res}    0.1550

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_UCDP_bi_1 {c |}{col 14}{res}{space 2} .3516677{col 26}{space 2} .0531036{col 37}{space 1}    6.62{col 46}{space 3}0.000{col 54}{space 4} .2475859{col 67}{space 3} .4557494
{txt}{space 2}idle_index {c |}{col 14}{res}{space 2} .0034172{col 26}{space 2} .0011385{col 37}{space 1}    3.00{col 46}{space 3}0.003{col 54}{space 4} .0011857{col 67}{space 3} .0056487
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0301663{col 26}{space 2}  .001665{col 37}{space 1}   18.12{col 46}{space 3}0.000{col 54}{space 4} .0269029{col 67}{space 3} .0334297
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}        0{col 39}{result}{space 1}    20244{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est2{txt} stored)

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:8.113068931259408}"

{com}. 
. eststo: reghdfe UCDP_bi wy_UCDP_bi_1 idle_index , absorb(objectid oyfe) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 2 HDFE groups{col 51}F({res}   2{txt},{res} 222682{txt}){col 67}= {res}     26.66
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4539
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4043
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0006
{txt}{col 51}Root MSE{col 67}= {res}    0.1550

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_UCDP_bi_1 {c |}{col 14}{res}{space 2} .3516677{col 26}{space 2} .0531036{col 37}{space 1}    6.62{col 46}{space 3}0.000{col 54}{space 4} .2475859{col 67}{space 3} .4557494
{txt}{space 2}idle_index {c |}{col 14}{res}{space 2} .0034172{col 26}{space 2} .0011385{col 37}{space 1}    3.00{col 46}{space 3}0.003{col 54}{space 4} .0011857{col 67}{space 3} .0056487
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0301663{col 26}{space 2}  .001665{col 37}{space 1}   18.12{col 46}{space 3}0.000{col 54}{space 4} .0269029{col 67}{space 3} .0334297
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
({res}est3{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:8.113068931259397}"

{com}. 
. eststo: reghdfe UCDP_bi wy_UCDP_bi_1 idle_index , absorb(objectid oyfe mon ) vce(r )  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 3 HDFE groups{col 51}F({res}   2{txt},{res} 222671{txt}){col 67}= {res}     26.71
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4543
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4046
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0007
{txt}{col 51}Root MSE{col 67}= {res}    0.1550

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_UCDP_bi_1 {c |}{col 14}{res}{space 2}  .367092{col 26}{space 2} .0555936{col 37}{space 1}    6.60{col 46}{space 3}0.000{col 54}{space 4}   .25813{col 67}{space 3}  .476054
{txt}{space 2}idle_index {c |}{col 14}{res}{space 2} .0035448{col 26}{space 2} .0011758{col 37}{space 1}    3.01{col 46}{space 3}0.003{col 54}{space 4} .0012404{col 67}{space 3} .0058493
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0296528{col 26}{space 2} .0017341{col 37}{space 1}   17.10{col 46}{space 3}0.000{col 54}{space 4}  .026254{col 67}{space 3} .0330516
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est4{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:8.416114956130855}"

{com}. 
. eststo: reghdfe UCDP_bi wy_UCDP_bi_1 idle_index temp prec, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   241,248
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res} 221129{txt}){col 67}= {res}     13.60
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4546
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4050
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0007
{txt}{col 51}Root MSE{col 67}= {res}    0.1554

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_UCDP_bi_1 {c |}{col 14}{res}{space 2} .3681374{col 26}{space 2} .0559117{col 37}{space 1}    6.58{col 46}{space 3}0.000{col 54}{space 4} .2585518{col 67}{space 3}  .477723
{txt}{space 2}idle_index {c |}{col 14}{res}{space 2} .0030747{col 26}{space 2} .0012906{col 37}{space 1}    2.38{col 46}{space 3}0.017{col 54}{space 4} .0005453{col 67}{space 3} .0056042
{txt}{space 8}temp {c |}{col 14}{res}{space 2} 4.91e-06{col 26}{space 2} .0000989{col 37}{space 1}    0.05{col 46}{space 3}0.960{col 54}{space 4} -.000189{col 67}{space 3} .0001988
{txt}{space 8}prec {c |}{col 14}{res}{space 2}-3.81e-06{col 26}{space 2} 3.93e-06{col 37}{space 1}   -0.97{col 46}{space 3}0.333{col 54}{space 4}-.0000115{col 67}{space 3} 3.90e-06
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0302513{col 26}{space 2} .0028405{col 37}{space 1}   10.65{col 46}{space 3}0.000{col 54}{space 4} .0246839{col 67}{space 3} .0358187
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      718{col 27}{space 1}        0{col 39}{result}{space 1}      718{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20104{col 27}{space 1}      718{col 39}{result}{space 1}    19386{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est5{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local TP "x"

{txt}added macro:
                 e(TP) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:7.300061084849054}"

{com}. 
. eststo: reghdfe UCDP_bi wy_UCDP_bi_1 idle_index py_UCDP_bi, absorb(objectid oyfe mon ) vce(r)  
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   242,928
{txt}Absorbing 3 HDFE groups{col 51}F({res}   3{txt},{res} 222670{txt}){col 67}= {res}    117.48
{txt}{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4594
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4102
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0101
{txt}{col 51}Root MSE{col 67}= {res}    0.1543

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     UCDP_bi{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
wy_UCDP_bi_1 {c |}{col 14}{res}{space 2} .3601772{col 26}{space 2} .0553661{col 37}{space 1}    6.51{col 46}{space 3}0.000{col 54}{space 4} .2516611{col 67}{space 3} .4686933
{txt}{space 2}idle_index {c |}{col 14}{res}{space 2}  .003536{col 26}{space 2} .0011685{col 37}{space 1}    3.03{col 46}{space 3}0.002{col 54}{space 4} .0012457{col 67}{space 3} .0058263
{txt}{space 2}py_UCDP_bi {c |}{col 14}{res}{space 2}  .019076{col 26}{space 2} .0011007{col 37}{space 1}   17.33{col 46}{space 3}0.000{col 54}{space 4} .0169186{col 67}{space 3} .0212333
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.1343301{col 26}{space 2} .0095835{col 37}{space 1}  -14.02{col 46}{space 3}0.000{col 54}{space 4}-.1531136{col 67}{space 3}-.1155466
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    objectid{col 14}{c |}{space 1}      723{col 27}{space 1}        0{col 39}{result}{space 1}      723{col 53}{text} {col 54}{c |}
{col 1}{text}        oyfe{col 14}{c |}{space 1}    20244{col 27}{space 1}      723{col 39}{result}{space 1}    19521{col 53}{text} {col 54}{c |}
{col 1}{text}       month{col 14}{c |}{space 1}       12{col 27}{space 1}        1{col 39}{result}{space 1}       11{col 53}{text}?{col 54}{c |}
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
({res}est6{txt} stored)

{com}. estadd local FEobj"x"

{txt}added macro:
              e(FEobj) : "{res:x}"

{com}. estadd local FEoy "x"

{txt}added macro:
               e(FEoy) : "{res:x}"

{com}. estadd local FEmo "x"

{txt}added macro:
               e(FEmo) : "{res:x}"

{com}. estadd local PY "x"

{txt}added macro:
                 e(PY) : "{res:x}"

{com}. estadd local perch =  (_b[idle_index]/`bl')*100

{txt}added macro:
              e(perch) : "{res:8.395229870116543}"

{com}. 
. #delimit ; 
{txt}delimiter now ;
{com}. esttab _all using "FigTbl/Appendix_TblA5_WYDV_UCDP.csv", label nogaps compress 
> keep(idle_index wy_UCDP_bi_1)  se star(* 0.05 ** 0.01 *** 0.001) 
> stats(perch N r2 FEobj FEoy FEmo TP PY, fmt(%3.2f %18.0g %12.2f) labels(`"Per. Change"' `"Observations"' `"R-squared"' `"Location FE"' `"Location-Year FE"' `"Calendar Month FE"' `"Temp & Precipitation"' `"Peace Months"') )
> replace ;
{res}{txt}(output written to {browse  `"FigTbl/Appendix_TblA5_WYDV_UCDP.csv"'})

{com}.  #delimit cr 
{txt}delimiter now cr
{com}. 
. 
{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}D:\Dropbox\Harvests and Protests\Data&code\PSRM_ReplicationSubmitted\LogFile.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}29 Sep 2023, 19:49:56
{txt}{.-}
{smcl}
{txt}{sf}{ul off}